Method of monitoring and analyzing surgical procedures

ABSTRACT

A surgical computing system may obtain monitored data associated with healthcare professionals (HCPs), surgical instruments and/or environments in one or more operating rooms (ORs). the surgical computing system may utilize the monitored data to enable aggregated efficiency analysis for multiple ORs, establishing and maintaining virtual boundaries in ORs, control access verification of hcps, adaptively controlling or systems, improving movement or motion efficiency for surgical procedures, and/or performing ergonomic monitoring and analysis for ORs. For example, procedure data associated with a surgical procedure plan in the operating room may be determined, and a surgical instrument anticipated for future use may be identified. The surgical computing system may determine, based on the monitored data associated with the instruments, the readiness of the identified surgical instrument anticipated for future use. The system may communicate an indication to prepare the identified surgical instrument to one or more HCPs inside and/or outside the OR.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of Provisional U.S. Patent Application No. 63/194,675 (attorney docket number END9339USPSP1), filed May 28, 2021, the disclosure of which is incorporated herein by reference in its entirety.

This application is related to the following, filed contemporaneously, the contents of each of which are incorporated by reference herein:

-   -   U.S. patent application, entitled AGGREGATED NETWORK OF SURGICAL         HUBS FOR EFFICIENCY ANALYSIS, with attorney docket number         END9339USNP2;     -   U.S. patent application, entitled MONITORING A HEALTH CARE         PROFESSIONAL MOVEMENT RELATIVE TO A VIRTUAL BOUNDARY IN AN         OPERATING ROOM, with attorney docket number END9339USNP3;     -   U.S. patent application, entitled CONTROL ACCESS VERIFICATION OF         A HEALTH CARE PROFESSIONAL, with attorney docket number         END93391USNP4;     -   U.S. patent application, entitled ADAPTIVE CONTROL OF OPERATING         ROOM SYSTEMS with attorney docket number END9339USNP5;     -   U.S. patent application, entitled EFFICIENCY OF MOTION         MONITORING AND ANALYSIS FOR A SURGICAL PROCEDURE with attorney         docket number END9339USNP6; and     -   U.S. patent application, entitled ERGONOMIC MONITORING AND         ANALYSIS FOR AN OPERATING ROOM with attorney docket number         END9339USNP7.

BACKGROUND

Successful surgeries depend on the expertise of several types of operating room (OR) team members. The roles of operating room personnel vary. In addition, surgeons make the critical decisions involved in directing the course of a procedure. Surgeons may perform the incisions involved in an operation. Anesthesiologists or nurse anesthetists may be in charge of safely administering anesthesia to patients prior to surgery, monitoring them during surgery and making sure that they safely come out of anesthesia after the operation. A circulating technician may bring the patient to the operating room, tie the surgical gowns of surgeons and other personnel, deliver needed additional supplies such as instruments and medicine, and document the surgery. Scrub technicians may sterilize instruments before and after the surgery, keep the surgical field organized during surgery, and provide the surgeon with needed instruments. Registered nurses may perform the duties typically associated with surgical technicians, including acting as circulating nurses and scrub nurses. In addition, a nurse may act as the first assistant to the surgeon. OR human traffic has been implicated as a cause of surgical site infection.

SUMMARY

A surgical computing system may obtain monitored data associated with movement of healthcare professionals (H CPs) in an operating room OR. The surgical computing system may obtain monitored data associated with movement of surgical instruments in the OR, and may determine parameter(s) associated with a recommended surgical instrument within the OR based at least in part on the monitored data. For example, procedure data associated with a surgical procedure plan in the operating room may be determined, and a surgical instrument anticipated for future use may be identified. The surgical computing system may determine, based on the monitored data associated with the instruments, the readiness of the identified surgical instrument anticipated for future use. The computing system may communicate an indication to prepare the identified surgical instrument to one or more HCPs inside and/or outside the OR.

A computing system may be configured to obtain and aggregate surgical monitoring data associated with multiple surgical procedures. The multiple surgical procedures may be associated with one or more operating rooms (ORs), and the surgical monitoring data may be obtained via one or more surgical hubs in the OR(s). Surgical resource utilization adjustment(s) may be generated based on the aggregated surgical resource monitoring data, and an output may be generated based on the determined surgical resource utilization adjustment. For example, resource allocation and utilization data and surgical outcome data across multiple ORs may be obtained and aggregated. The aggregated data may be used to generate resource allocation adjustment(s) for the ORs. Resource allocation adjustment(s) may include, but not limited to, healthcare personnel (HCP) assignment adjustment(s), surgery scheduling adjustment(s), surgical instrument allocation adjustment(s), OR layout adjustment(s), and/or medical facility layout adjustment(s), etc.

For example, the surgical monitoring data may include surgical resource monitoring data, HCP monitoring data, surgical instrument utilization data, and/or surgical procedure progression data associated with multiple surgical procedures that may take place in multiple ORs. The surgical monitoring data may include instrument stock and utilization data, OR turnover data and/or cost data associated with the surgical procedures. HCP efficiency may be analyzed based on the aggregated OR utilization data, the aggregated OR turnover data, the aggregated HCP reposition data, and/or the aggregated instrument exchange data associated with the plurality of surgical procedures.

Procedure summary information associated with multiple ORs may be generated based on the aggregated surgical monitoring data. Procedure summary information may include planned, actual and projected HCP assignment information, planned, actual and projected surgical step information, and/or planned, actual and projected surgical resource information.

The computing system may generate an output based on the determined adjustment(s). The output may include, but not limited to, a control signal for adjusting an HCP assignment, adjusting surgery scheduling, adjusting surgical instrument allocation, adjusting surgical plan(s), notifying HCPs and/or administrators of surgical resource adjustments, notifying potential issues and/or providing recommendations.

For example, a set of repetitive trips may be identified based on the aggregated HCP monitoring data, and surgical tasks associated with the set of repetitive trips may be identified based on the aggregated surgical procedure progression data associated with the surgical procedures. HCP task assignment adjustment(s) may be determined for reducing the distance traveled associated with the identified surgical tasks. For example, a set of combinable tasks may be identified, from the surgical tasks associated with the repetitive trips, based on the aggregated surgical procedure progression data. The computing system may generate an output to indicate the combinable tasks. For example, aspect(s) of OR layout associated with the identified repetitive trips may be identified, and OR layout adjustment(s) may be generated such that a path length associated with the set of repetitive trips may be reduced.

Surgical procedure planning data associated with multiple surgical procedures may be from multiple surgical hubs and may be used to generate updated surgical procedure plans based on the surgical procedure progression data with the surgical procedures. Planned HCP task assignment associated with the surgical procedures may be obtained and updated based on the updated surgical procedure plans and the HCP monitoring data associated with surgical procedures. Surgical instrument allocation data associated with the surgical procedures may be obtained and, predicted or projected surgical instrument utilization data associated with the surgical procedures may be determined based on the aggregated surgical instrument utilization monitoring data and the updated surgical procedure plans.

For example, the computing system may assign a task to HCP(s) based on the aggregated surgical monitoring data. The computing system may predict that the task is to be performed during a time period. An HCP's energy level and/or fatigue level during the time period may be projected based on the biomarker measurement data associated with the HCP, and the availability of the HCP during time period may be determined based on the surgical procedure planning data and the surgical procedure progress data. Whether to assign the task to the HCP may be determined based on the projected fatigue level and the availability of the HCP during the time period.

A computing system may determine a virtual boundary associated with a restricted access area in an operating room (OR). A virtual boundary associated with a restricted access area in an OR may be associated with an area for a surgical instrument, an area surrounding a patient, a surgical table, a sterile field area, a filtration system, a particle capture system, an airborne contamination zone, an area associated with an anesthesiologist equipment, or an area associated with a health care professional (HCP), such as a surgeon, an anesthesiologist, a scrub nurse, a circulating nurse, or an observer. The computing system may provide a visual indication about the location of the virtual boundary. For example, the computing system may utilize a laser device to outline a virtual boundary are onto a floor of the OR.

A computing system may identify an HCP in an OR. The computing system may identify an HCP in an OR based on a facial recognition, a RFID tag associated with the HCP, and/or the like. During a surgical procedure, an HCP may move around or within an OR. The computing system may monitor a movement associated with the identified HCP.

The computing system may determine an access authorization information associated with the identified HCP. For example, the computing system may determine whether the HCP has an access authorization to enter, exit, interact with, or be inside of a virtual boundary of a restricted access area. The computing system may determine an access authorization for the HCP based on an HCP role during a surgical procedure, an assignment associated with the HCP during the surgical procedure, a personal protective equipment (PPE) associated with the HCP, a biomarker measurement associated with the HCP, a restricted area type, or certificate associated with the HCP.

The computing system may determine that the HCP is in a proximity to the virtual boundary area. For example, based on the monitored movement of the HCP, the computing system may determine whether the HCP is in proximity to the virtual boundary area or whether the HCP is approaching the virtual boundary area. The computing system may determine whether the HCP is authorized to enter the virtual boundary. For example, the computing system may determine an access authorization information of the HCP and may determine whether the HCP is authorized or unauthorized to enter or interact with the virtual boundary area. If the computing system determines that the HCP is in a proximity to the virtual boundary area and is unauthorized to be in the proximity to the virtual boundary area, the computing system may send a notification to the HCP. The notification may indicate that the HCP is unauthorized to enter or interact with the virtual boundary area. The notification may prevent an inadvertent interaction with the virtual boundary area by an unauthorized HCP.

The computing system may send the notification to a device associated with the HCP. The notification may be or may include one or more of a visual notification, an audio notification, a haptic notification, or an augmented reality notification. The computing system may send a notification to a display in the OR. For example, if the computing system determines that the unauthorized HCP is approaching the virtual boundary area and/or is about to enter or interact with the virtual boundary area, the computing system may send a notification to the display in the OR to notify one or more other HCPs in the OR.

A computing system may determine a virtual boundary of a restricted access area associated with a surgical instrument. The computing system may detect a location of a surgical instrument and monitor the movement of the surgical instrument during a surgical procedure. If the computing system determines that the surgical instrument has moved or repositioned, the computing system may adjust the virtual boundary area of the surgical instrument accordingly. The computing system may monitor an energized state of the surgical instrument. The computing system may adjust the virtual boundary of the surgical instrument area based on the detected energy state of the surgical instrument. For example, the computing system may increase the virtual boundary area of the surgical instrument if the computing system detects a high energized state (e.g., above a threshold level). The computing system may decrease the virtual boundary area of the surgical instrument if the computing system detects a low energized state (e.g., below a threshold lever).

The computing system may identify and/or monitor a surgical step. For example, the computing system may identify a current surgical step or an upcoming surgical step. Based on the identified surgical step, the computing system may adjust the virtual boundary. For example, during a surgical step, a body of a patient may be repositioned. The body of the patient may be moved to a side for a current surgical step. The computing system may adjust the virtual boundary area associated with the patient based on the reposition of the body of the patient, e.g., according to the surgical step.

A computing system may receive an access authorization adjustment request of an HCP from one or more other HCPs in the OR. In examples, a lead surgeon may increase or decrease the access authorization of an HCP. In examples, during an emergency, a computing system may adjust the access authorization of an HCP. Based on the emergency situation and/or a request from another HCP, a previously unauthorized HCP may have access to enter, exit, or be within the virtual boundary of a restricted access area.

A computing system may identify a surgical instrument associated with a surgical procedure in an operating room (OR). During a surgical operation, the computing system may detect a control input by a health care professional (HCP) to control the surgical instrument. The control input by the HCP may be turning on/off the surgical instrument, increase/decrease an energized state of the surgical instrument, and/or the like. If the computing system detects a control input by the HCP, the computing system may determine whether the HCP is authorized to provide the control input to control the surgical instrument. For example, the computing system may determine the HCP's access control level associated with the surgical instrument. The control level may provide information about whether the HCP is authorized to control the surgical instrument. In examples, the control level may indicate that the HCP is unauthorized to control the surgical instrument. In examples, the control level may indicate that the HCP is authorized to control the surgical instrument. The access control level may provide information about whether the HCP has a full control to control a surgical instrument. The access control level may provide information about whether the HCP has a partial control to control a surgical instrument (e.g., limited to turning on/off the surgical instrument). For example, the access control level for the HCP may be tiered. A lower-tiered access control level may allow/authenticate the HCP to turn on/off the surgical instrument. A higher-tiered access control may allow/authenticate the HCP to adjust an energized state of the surgical instrument.

The computing system may effectuate the control input by the HCP if the computing system determines that the HCP is authorized to control the surgical instrument. For example, if the computing system determines that the HCP is unauthorized to control the surgical instrument, the computing system may block the control input by the HCP. If the computing system determines that the HCP is authorized to control the surgical instrument, the computing system may effectuate the control input by the HCP.

The computing system may send an alert to the HCP. The alert may notify the HCP whether the HCP is authorized or unauthorized to control the surgical instrument. The alert may also notify the HCP whether the control input has been effectuated or blocked, e.g., based on the control access level associated with the HCP. The alert may be or may include one or more of a virtual alert, an audible alert, a haptic alert, or an augmented reality alert.

The computing system may adjust the HCP's control access level. The computing system may adjust the control level of the HCP based on a proximity to and/or within a virtual boundary of restricted access area. For example, if the HCP is unauthorized to control a surgical instrument and the computing system determines that the HCP is within a virtual boundary area of an operating table and/or a virtual boundary area of a surgeon, the computing system may adjust the control access level of the HCP and provide a partial authorization to control the surgical instrument (e.g., turning on/off the surgical instrument).

The computing system may adjust a control access level of an HCP based on a request from other HCP(s) in the OR. For example, if the computing system blocks a control input by the HCP, such as a scrub nurse, the computing system may send a message to other HCP in the OR, such as a surgeon. The message may be or may include an access control level adjustment message. If the other HCP, such as the surgeon, determines that the scrub nurse should be able to control the surgical instrument, e.g., turning on the surgical instrument before handing the instrument to the surgeon, the surgeon may send an access control level adjustment request to the computing system. The computing system may, based on receiving the access control level adjustment request from the surgeon, adjust the access control of the scrub nurse. The computing system may send a notification, such as an access control level adjustment notification, to the HCP. The notification may notify the HCP that the access control level associated with the HCP has been adjusted by other HCP, such as the surgeon.

The computing system may adjust a control access level of an HCP based on a surgical step in a surgical procedure. The computing system may identify a current surgical step in the surgical procedure. Based on the current surgical step, the computing system may adjust the control access level of the HCP. For example, to prevent an inadvertent control of a surgical instrument, the computing system may adjust the control access level of the HCP when the computing system determines the current surgical step matches with operating the surgical instrument. The computing system may block the control input by the HCP in other surgical steps.

The computing system may adjust a control access level of an HCP based on an energized state of a surgical instrument. The computing system may determine whether the surgical instrument is in a low energized state or a high energized state. The computing system may block a control input by the HCP if the surgical instrument is in a high energized state. The computing system may effectuate the control input by the HCP if the surgical instrument is in a low energized state.

The computing system may adjust a control access level of an HCP based on biomarker measurements associated with the HCP. For example, the computing system may monitor one or more biomarker of the HCP. If the computing system detects an elevated and/or an increased stress level or a fatigue level of the HCP, the computing system may adjust the control access level of the HCP by blocking a control input by the HCP. The computing system may adjust the control access level of the HCP by effectuating the control input by the HCP if the computing system detects an acceptable stress level and/or an acceptable fatigue level of the HCP.

Systems, methods, and instrumentalities are disclosed for adaptive control of operating room systems based upon monitored data associated with the operating room. Data relating to, for example, the patient receiving treatment in the operating room, healthcare professionals working in the operating room, environmental readings in the operating room, and/or activity in the operating room may be collected and communicated to a surgical computing system. The surgical computing system may obtain the data, which may be referred to as monitored data, and may determine, based upon the monitored data, parameters for controlling various systems associated with the operating room. The surgical computing system may communicate the parameters to the systems which may modify their operation based upon the received parameters.

The surgical computing system may be configured to analyze monitored data to identify the occurrence of particular surgical events, and to control one or more operating room systems based upon detection that a surgical event is taking or has taken place. The surgical computing system may determine, based on the monitored data, that a particular surgical event, such as, for example, a significant step in a surgical procedure is being undertaken. The surgical computing system, based upon the monitored data and in view of the surgical event being undertaken, may determine parameters to modify operation of operating room systems. The surgical computing system may determine parameters for controlling the display of data on a display monitor used by the healthcare professionals performing the surgical procedure. The parameters may control the display monitor to highlight or emphasize on the display particular patient biomarker data that is relevant to the surgical event.

The surgical computing system may be configured to analyze monitored data and may determine, based upon the monitored data, parameters for adaptively controlling lighting systems in the operating room. The surgical computing system may obtain monitored data associated with one or more healthcare professionals in the operating room. The monitored data may comprise data associated with the focus of a healthcare professional, the location of the healthcare professional, and/or the activity of the healthcare professional. The monitored data may further comprise data associated with the surgical task that is being undertaken. The surgical computing system may determine, based on the monitored data, parameters for controlling or adjusting lighting systems in the operating room. For example, the surgical computing system may determine parameters that result in one or more lighting systems decreasing or increasing intensity depending upon the environment in the operating room as indicated by the monitored data.

The surgical computing system may be configured to analyze monitored data and may determine, based upon the monitored data, parameters for adaptively controlling air handling systems in the operating room. The surgical computing system may obtain monitored data that may be associated with, for example, air quality and/or air particulates in the air in the operating room. The surgical computing system may determine, based on the monitored data, parameters for controlling or adjusting operation of air handling and filtration systems. The parameters may adjust operating room systems that perform surgical insulation, smoke evacuation, and/or air filtration.

The surgical computing system may be configured to analyze monitored data and may determine, based upon the monitored data, parameters for adaptively controlling heating and/or cooling control systems associated with the operating room. The surgical computing system may obtain monitored data that may be associated with, for example, patient and/or healthcare professional's biomarkers. The surgical computing system may determine, based on the monitored data, that one or more temperatures associated with the operating room, patient, and/or healthcare providers is relatively high or low. The surgical computing system may determine parameters for controlling the heating and/or cooling systems associated with the operating room so as to raise and/or lower a particular temperature. The heating and/or cooling systems may be ambient and/or local control systems.

The surgical computing system may be configured to analyze monitored data and may determine, based upon the monitored data, parameters for adaptively controlling operating room systems to implement room conditions associated with a particular healthcare provider who may be participating in the ongoing surgical procedure. The surgical computing system may determine the monitored data may indicate or are associated with a particular step, e.g., a significant or critical step, of a surgical procedure. If the surgical computing system determines the monitored data indicate a particular step in a surgical procedure is being performed, the surgical computing system may determine parameters for operating room systems associated with preferred room conditions for a particular healthcare professional. The surgical computing system may be configured to determine parameters that implement hierarchical priority based adjustments to equipment based on situational awareness and importance of a step in a surgical procedure.

The surgical computing system may be configured to analyze monitored data and may determine, based on the monitored data, parameters for adaptively controlling operating room environment control systems. The surgical computing system may determine to generate parameters associated with adjusting, for example, one or more of the intensity, duration, and/or rapidity of operation of environmental control devices. For example, the surgical computing system may determine to generate parameters associated with the intensity of operation of an air flow control system. The surgical computing system may apply thresholds to considering the monitored data and may adjust the thresholds that the surgical computing system may apply over time based on the importance of the measure to the patient or a healthcare professional.

Systems, methods, and instrumentalities are disclosed for monitoring healthcare professionals (HCPs) in a surgical procedure and providing parameters associated with improving performance for surgical procedure(s) and/or maintenance of operating room(s). The parameters may include recommendations, adjustments, feedback, and/or control signals. The parameters may be associated with positioning, such as operating room (OR) layout, surgical equipment positioning, and/or the like. For example, a computing system may monitor HCP motion and interactions, and perform an analysis of HCP motion and interactions throughout a procedure. The computing system may perform an analysis of HCP motion and interactions throughout a procedure to identify improvements for positioning, OR layout, surgical instrument mix, access to the surgical site, and/or the like.

The computing system may record one or more of HCP motion, HCP activities, HCP, surgical instrument exchange, surgical instrument positioning, and/or the like. The computing system may analyze one or more of the HCP motion, HCP activities, HCP, surgical instrument exchange, surgical instrument positioning, and/or the like. The system may record and analyze one or more of the HCP motion, HCP activities, HCP, surgical instrument exchange, surgical instrument positioning, and/or the like to generate positioning parameters. The positioning parameters may include one or more of an OR layout, surgical instrument positioning, surgical site access positioning, camera positioning, display positioning, and/or the like.

For example, the computing system may obtain monitored data associated with an operating room. The monitored data may include data associated with one or more of HCP motion, HCP interactions, OR layout, surgical equipment location, surgical instrument mix, or surgical site access. The computing system may obtain procedure data associated with the surgical procedure plan. The computing system may determine one or more positioning parameters associated with a system associated with the operating room. The positioning parameters may include adjustments to one or more of OR layout, surgical instrument mix, surgical equipment positioning, and/or the like. The computing system may determine one or more adjustment parameters associated with HCP actions, HCP staffing, and/or the like. The computing system may communicate the positioning and/or adjustment parameters, for example, to one or more systems associated with the operating room.

Systems, methods, and instrumentalities are disclosed for monitoring HCPs in a surgical procedure and providing parameters associated with improving wear on HCPs. The parameters may be indicated in control signals, recommendations, adjustments, and/or feedback. The parameters may be associated with ergonomic positioning. For example, a computing system may monitor surgeon motion, posture, and surgical access to create recommendations to improve wear on HCPs.

A computing system may analyze motions and postures of HCPs, for example, throughout a surgical procedure. The computing system may analyze motions and postures of HCPs throughout a procedure to identify improvements for posture, weightlifting, standing, and the like. The computing system may record one or more of a patient position, a surgeon access location, and a surgeon access orientation. The computing system may analyze one or more of the patient position, surgeon access location, and/or surgeon access orientation. The computing system may record and analyze one or more of the patient position, surgeon access location, and/or surgeon access orientation to generate parameters. The parameters may minimize repositioning and awkward positions and postures. The parameters may include one or more of an instrument mix selection, a trocar location, an OR table setup, or a patient positioning. For example, the computing system may obtain monitored data associated with an operating room. The monitored data may include data associated with one or more of OR layout, surgical equipment location, patient positioning, surgical instrument mix, surgical device positioning, HCP motion(s), HCP posture(s), physical trait(s) of HCP(s), the head and/or eye position(s) of HCP(s), or surgical display positioning. The computing system may determine one or more ergonomic adjustment parameters associated with ergonomic positioning within the operating room based on the monitored data. The ergonomic adjustment parameter(s) may include adjustments to one or more of OR layout, patient positioning, surgical display operation, surgical equipment location and/or the like. The computing system may send an indication of the ergonomic adjustment parameter(s). The computing system may communicate the ergonomic adjustment parameter(s) associated with ergonomic positioning to one or more systems associated with the operating room. For example, the computing system may communicate the adjustment parameter(s) to a system configured to control surgical display(s) in the OR. The surgical display may present the ergonomic adjustment parameters. The system configured to control surgical display(s) may modify the positioning or settings of one or more surgical display(s), for example, based on the ergonomic adjustment parameters.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a computer-implemented healthcare personnel (HCP) monitoring system.

FIG. 2 shows an example of an HCP monitoring system in a surgical operating room.

FIG. 3 illustrates an example surgical hub paired with various systems.

FIG. 4 illustrates a surgical data network having a set of communication surgical hubs configured to connect with a set of sensing systems, an environmental sensing system, a set of devices, etc.

FIG. 5 illustrates an example computer-implemented interactive surgical system that may be part of an HCP monitoring system.

FIG. 6 illustrates a logic diagram of a control system of a surgical instrument.

FIG. 7 shows an exemplary sensing system with a sensor unit and a data processing and communication unit.

FIG. 8 illustrates an exemplary timeline of an illustrative surgical procedure indicating adjusting operational parameters of a surgical device based on a surgeon biomarker level.

FIG. 9 is a block diagram of the computer-implemented interactive HCP monitoring system.

FIG. 10 shows an example surgical system having a surgical instrument in communication with a console or a portable device.

FIG. 11 is a diagram of an example situationally aware surgical system.

FIG. 12 shows an example surgical monitoring and analysis.

FIG. 13 shows an example surgical monitoring and aggregated analysis across multiple operating rooms.

FIG. 14 shows example display summarizing surgical procedures, HCP, surgical device stock status, highlighting deficiencies and recommending remediations across multiple operating rooms.

FIG. 15 shows an example efficiency analysis based on surgical monitoring data.

FIG. 16 shows an example efficiency analysis based on aggregated surgical monitoring data across multiple ORs.

FIG. 17 shows an example updating of surgical procedural plans based on surgical monitoring data.

FIG. 18 shows an example adjustments of HCP assignments based on aggregated surgical monitoring data across multiple ORs.

FIG. 19 illustrates examples of one or more virtual boundaries associated with restricted accesses in an operating room (OR).

FIG. 20 illustrates examples of one or more virtual boundaries associated with restricted accesses in an OR.

FIG. 21 illustrates examples of a constant virtual boundary, a selective virtual boundary, or an adaptive virtual boundary in an OR

FIG. 22 illustrates example virtual boundary associated with a surgical instrument.

FIG. 23 illustrates an example notification of a computing system for an unauthorized energy level change of a surgical instrument.

FIG. 24 illustrates an example flow of monitoring an HCP movement relative to a virtual boundary of restricted access area in an OR.

FIG. 25 illustrates an example flow of control access verification of an HCP in an OR.

FIG. 26 is a flow diagram of example processing associated with monitoring an operating room and determining parameters.

FIG. 27 illustrates example timing charts of example adaptive control of lighting systems based on monitored operating room data.

FIG. 28 illustrates an example graph of performed surgical procedures plotted based on outcome success and efficiency.

FIG. 29 illustrates example processing associated with monitoring an operating room and determining parameters associated with improving performance of surgical procedure(s) and/or maintenance of the OR.

FIG. 30 illustrates an example OR layout and HCP activity during a surgical procedure.

FIG. 31 illustrates an example OR layout and HCP activity during a surgical procedure.

FIG. 32 illustrates a flow diagram of an example processing associated with monitoring an operating room and determining parameters.

FIG. 33 illustrates an example display position within an operating room.

FIG. 34 illustrates an example operating room that includes a surveillance system monitoring head and eye positioning of healthcare professionals.

FIG. 35 illustrates an example display in an operating room that may pivot positioning and orientation between healthcare professionals.

DETAILED DESCRIPTION

FIG. 1 is a block diagram of a computer-implemented HCP monitoring system 20000. An example HCP monitoring system such as the HCP monitoring system 20000 may include one or more HCP monitoring systems (e.g., HCP monitoring sub-systems) 20002, 20003 and 20004. For example, HCP monitoring system 20002 may include a computer-implemented interactive surgical system. For example, HCP monitoring system 20002 may include at least one of the following: a surgical hub 20006 in communication with a cloud computing system 20008, for example, as described in FIG. 2 . An HCP monitoring system may include at least one of the following: a surgical hub 20006 or a computing device 20016 in communication with a could computing system 20008. The cloud computing system 20008 may include at least one remote cloud server 20009 and at least one remote cloud storage unit 20010. Example HCP monitoring systems 20002, 20003, or 20004 may include a wearable sensing system 20011, an environmental sensing system 20015, a robotic system 20013, one or more intelligent instruments 20014, human interface system 20012, etc. The human interface system is also referred herein as the human interface device. The wearable sensing system 20011 may include one or more HCP sensing systems, and/or one or more patient sensing systems. The environmental sensing system 20015 may include one or more devices, for example, used for measuring one or more environmental attributes, for example, as further described in FIG. 2 . The robotic system 20013 may include a plurality of devices used for performing a surgical procedure, for example, as further described in FIG. 2 .

The HCP monitoring system 20002 may be in communication with a remote server 20009 that may be part of a cloud computing system 20008. In an example, HCP monitoring system 20002 may be in communication with a remote server 20009 via an internet service provider's cable/FIOS networking node. In an example, a patient sensing system may be in direct communication with a remote server 2009. The HCP monitoring system 20002 and/or a component therein may communicate with the remote servers 20009 via a cellular transmission/reception point (TRP) or a base station using one or more of the following cellular protocols: GSM/GPRS/EDGE (2G), UMTS/HSPA (3G), long term evolution (LTE) or 4G, LTE-Advanced (LTE-A), new radio (NR) or 5G.

A surgical hub 20006 may have cooperative interactions with one of more means of displaying the image from the laparoscopic scope and information from one or more other smart devices and one or more sensing systems 20011. The surgical hub 20006 may interact with one or more sensing systems 20011, one or more smart devices, and multiple displays. The surgical hub 20006 may be configured to gather measurement data from the one or more sensing systems 20011 and send notifications or control messages to the one or more sensing systems 20011. The surgical hub 20006 may send and/or receive information including notification information to and/or from the human interface system 20012. The human interface system 20012 may include one or more human interface devices (HIDs). The surgical hub 20006 may send and/or receive notification information or control information to audio, display and/or control information to various devices that are in communication with the surgical hub.

For example, the sensing systems 20001 may include the wearable sensing system 20011 (which may include one or more HCP sensing systems and one or more patient sensing systems) and the environmental sensing system 20015 as discussed in FIG. 1 . The one or more sensing systems 20001 may measure data relating to various biomarkers. The one or more sensing systems 20001 may measure the biomarkers using one or more sensors, for example, photosensors (e.g., photodiodes, photoresistors), mechanical sensors (e.g., motion sensors), acoustic sensors, electrical sensors, electrochemical sensors, thermoelectric sensors, infrared sensors, etc. The one or more sensors may measure the biomarkers as described herein using one of more of the following sensing technologies: photoplethysmography, electrocardiography, electroencephalography, colorimetry, impedimentary, potentiometry, amperometry, etc.

The biomarkers measured by the one or more sensing systems 20001 may include, but are not limited to, sleep, core body temperature, maximal oxygen consumption, physical activity, alcohol consumption, respiration rate, oxygen saturation, blood pressure, blood sugar, heart rate variability, blood potential of hydrogen, hydration state, heart rate, skin conductance, peripheral temperature, tissue perfusion pressure, coughing and sneezing, gastrointestinal motility, gastrointestinal tract imaging, respiratory tract bacteria, edema, mental aspects, sweat, circulating tumor cells, autonomic tone, circadian rhythm, and/or menstrual cycle.

The biomarkers may relate to physiologic systems, which may include, but are not limited to, behavior and psychology, cardiovascular system, renal system, skin system, nervous system, gastrointestinal system, respiratory system, endocrine system, immune system, tumor, musculoskeletal system, and/or reproductive system. Information from the biomarkers may be determined and/or used by the computer-implemented patient and HCP monitoring system 20000, for example. The information from the biomarkers may be determined and/or used by the computer-implemented patient and HCP monitoring system 20000 to improve said systems and/or to improve patient outcomes, for example. The one or more sensing systems 20001, biomarkers 20005, and physiological systems are described in more detail in U.S. application Ser. No. 17/156,287 (attorney docket number END9290USNP1), titled METHOD OF ADJUSTING A SURGICAL PARAMETER BASED ON BIOMARKER MEASUREMENTS, filed Jan. 22, 2021, the disclosure of which is herein incorporated by reference in its entirety.

FIG. 2 shows an example of an HCP monitoring system 20002 in a surgical operating room. As illustrated in FIG. 2 , a patient is being operated on by one or more health care professionals (HCPs). The HCPs are being monitored by one or more HCP sensing systems 20020 worn by the HCPs. The HCPs and the environment surrounding the HCPs may also be monitored by one or more environmental sensing systems including, for example, a set of cameras 20021, a set of microphones 20022, and other sensors, etc. that may be deployed in the operating room. The HCP sensing systems 20020 and the environmental sensing systems may be in communication with a surgical hub 20006, which in turn may be in communication with one or more cloud servers 20009 of the cloud computing system 20008, as shown in FIG. 1 . The environmental sensing systems may be used for measuring one or more environmental attributes, for example, HCP position in the surgical theater, HCP movements, ambient noise in the surgical theater, temperature/humidity in the surgical theater, etc.

As illustrated in FIG. 2 , a primary display 20023 and one or more audio output devices (e.g., speakers 20019) are positioned in the sterile field to be visible to an operator at the operating table 20024. In addition, a visualization/notification tower 20026 is positioned outside the sterile field. The visualization/notification tower 20026 may include a first non-sterile human interactive device (HID) 20027 and a second non-sterile HID 20029, which may face away from each other. The HID may be a display or a display with a touchscreen allowing a human to interface directly with the HI). A human interface system, guided by the surgical hub 20006, may be configured to utilize the HIDs 20027, 20029, and 20023 to coordinate information flow to operators inside and outside the sterile field. In an example, the surgical hub 20006 may cause an HID (e.g., the primary HID 20023) to display a notification and/or information about the patient and/or a surgical procedure step. In an example, the surgical hub 20006 may prompt for and/or receive input from personnel in the sterile field or in the non-sterile area. In an example, the surgical hub 20006 may cause an HID to display a snapshot of a surgical site, as recorded by an imaging device 20030, on a non-sterile HID 20027 or 20029, while maintaining a live feed of the surgical site on the primary HID 20023. The snapshot on the non-sterile display 20027 or 20029 can permit a non-sterile operator to perform a diagnostic step relevant to the surgical procedure, for example.

In one aspect, the surgical hub 20006 may be configured to route a diagnostic input or feedback entered by a non-sterile operator at the visualization tower 20026 to the primary display 20023 within the sterile field, where it can be viewed by a sterile operator at the operating table. In one example, the input can be in the form of a modification to the snapshot displayed on the non-sterile display 20027 or 20029, which can be routed to the primary display 20023 by the surgical hub 20006.

Referring to FIG. 2 , a surgical instrument 20031 is being used in the surgical procedure as part of the HCP monitoring system 20002. The hub 20006 may be configured to coordinate information flow to a display of the surgical instrument 20031. For example, in U.S. Patent Application Publication No. US 2019-0200844 A1 (U.S. patent application Ser. No. 16/209,385), titled METHOD OF HUB COMMUNICATION, PROCESSING, STORAGE AND DISPLAY, filed Dec. 4, 2018, the disclosure of which is herein incorporated by reference in its entirety. A diagnostic input or feedback entered by a non-sterile operator at the visualization tower 20026 can be routed by the hub 20006 to the surgical instrument display within the sterile field, where it can be viewed by the operator of the surgical instrument 20031. Example surgical instruments that are suitable for use with the HCP monitoring system 20002 are described under the heading “Surgical Instrument Hardware” and in U.S. Patent Application Publication No. US 2019-0200844 A1 (U.S. patent application Ser. No. 16/209,385), titled METHOD OF HUB COMMUNICATION, PROCESSING, STORAGE AND DISPLAY, filed Dec. 4, 2018, the disclosure of which is herein incorporated by reference in its entirety, for example.

FIG. 2 illustrates an example of an HCP monitoring system 20002 being used to perform a surgical procedure on a patient who is lying down on an operating table 20024 in a surgical operating room 20035. A robotic system 20034 may be used in the surgical procedure as a part of the HCP monitoring system 20002. The robotic system 20034 may include a surgeon's console 20036, a patient side cart 20032 (surgical robot), and a surgical robotic hub 20033. The patient side cart 20032 can manipulate at least one removably coupled surgical tool 20037 through a minimally invasive incision in the body of the patient while the surgeon views the surgical site through the surgeon's console 20036. An image of the surgical site can be obtained by a medical imaging device 20030, which can be manipulated by the patient side cart 20032 to orient the imaging device 20030. The robotic hub 20033 can be used to process the images of the surgical site for subsequent display to the surgeon through the surgeon's console 20036.

Other types of robotic systems can be readily adapted for use with the HCP monitoring system 20002. Various examples of robotic systems and surgical tools that are suitable for use with the present disclosure are described in U.S. Patent Application Publication No. US 2019-0201137 A1 (U.S. patent application Ser. No. 16/209,407), titled METHOD OF ROBOTIC HUB COMMUNICATION, DETECTION, AND CONTROL, filed Dec. 4, 2018, the disclosure of which is herein incorporated by reference in its entirety.

Various examples of cloud-based analytics that are performed by the cloud computing system 20008, and are suitable for use with the present disclosure, are described in U.S. Patent Application Publication No. US 2019-0206569 A1 (U.S. patent application Ser. No. 16/209,403), titled METHOD OF CLOUD BASED DATA ANALYTICS FOR USE WITH THE HUB, filed Dec. 4, 2018, the disclosure of which is herein incorporated by reference in its entirety.

In various aspects, the imaging device 20030 may include at least one image sensor and one or more optical components. Suitable image sensors may include, but are not limited to, Charge-Coupled Device (CCD) sensors and Complementary Metal-Oxide Semiconductor (CMOS) sensors.

The optical components of the imaging device 20030 may include one or more illumination sources and/or one or more lenses. The one or more illumination sources may be directed to illuminate portions of the surgical field. The one or more image sensors may receive light reflected or refracted from the surgical field, including light reflected or refracted from tissue and/or surgical instruments.

The one or more illumination sources may be configured to radiate electromagnetic energy in the visible spectrum as well as the invisible spectrum. The visible spectrum, sometimes referred to as the optical spectrum or luminous spectrum, is that portion of the electromagnetic spectrum that is visible to (i.e., can be detected by) the human eye and may be referred to as visible light or simply light. A typical human eye will respond to wavelengths in air that range from about 380 nm to about 750 nm.

The invisible spectrum (e.g., the non-luminous spectrum) is that portion of the electromagnetic spectrum that lies below and above the visible spectrum (i.e., wavelengths below about 380 nm and above about 750 nm). The invisible spectrum is not detectable by the human eye. Wavelengths greater than about 750 nm are longer than the red visible spectrum, and they become invisible infrared (IR), microwave, and radio electromagnetic radiation. Wavelengths less than about 380 nm are shorter than the violet spectrum, and they become invisible ultraviolet, x-ray, and gamma ray electromagnetic radiation.

In various aspects, the imaging device 20030 is configured for use in a minimally invasive procedure. Examples of imaging devices suitable for use with the present disclosure include, but are not limited to, an arthroscope, angioscope, bronchoscope, choledochoscope, colonoscope, cytoscope, duodenoscope, enteroscope, esophagogastro-duodenoscope (gastroscope), endoscope, laryngoscope, nasopharyngo-neproscope, sigmoidoscope, thoracoscope, and ureteroscope.

The imaging device may employ multi-spectrum monitoring to discriminate topography and underlying structures. A multi-spectral image is one that captures image data within specific wavelength ranges across the electromagnetic spectrum. The wavelengths may be separated by filters or by the use of instruments that are sensitive to particular wavelengths, including light from frequencies beyond the visible light range, e.g., IR and ultraviolet. Spectral imaging can allow extraction of additional information that the human eye fails to capture with its receptors for red, green, and blue. The use of multi-spectral imaging is described in greater detail under the heading “Advanced Imaging Acquisition Module” in U.S. Patent Application Publication No. US 2019-0200844 A1 (U.S. patent application Ser. No. 16/209,385), tided METHOD OF HUB COMMUNICATION, PROCESSING, STORAGE AND DISPLAY, filed Dec. 4, 2018, the disclosure of which is herein incorporated by reference in its entirety. Multi-spectrum monitoring can be a useful tool in relocating a surgical field after a surgical task is completed to perform one or more of the previously described tests on the treated tissue. It is axiomatic that strict sterilization of the operating room and surgical equipment is required during any surgery. The strict hygiene and sterilization conditions required in a “surgical theater,” i.e., an operating or treatment room, necessitate the highest possible sterility of all medical devices and equipment. Part of that sterilization process is the need to sterilize anything that comes in contact with the patient or penetrates the sterile field, including the imaging device 20030 and its attachments and components. It will be appreciated that the sterile field may be considered a specified area, such as within a tray or on a sterile towel, that is considered free of microorganisms, or the sterile field may be considered an area, immediately around a patient, who has been prepared for a surgical procedure. The sterile field may include the scrubbed team members, who are properly attired, and all furniture and fixtures in the area.

Wearable sensing system 20011 illustrated in FIG. 1 may include one or more sensing systems, for example, HCP sensing systems 20020 as shown in FIG. 2 . The HCP sensing systems 20020 may include sensing systems to monitor and detect a set of physical states and/or a set of physiological states of a healthcare personnel (HCP). An HCP may be a surgeon or one or more healthcare personnel assisting the surgeon or other healthcare service providers in general. In an example, a sensing system 20020 may measure a set of biomarkers to monitor the heart rate of an HCP. In an example, a sensing system 20020 worn on a surgeon's wrist (e.g., a watch or a wristband) may use an accelerometer to detect hand motion and/or shakes and determine the magnitude and frequency of tremors. The sensing system 20020 may send the measurement data associated with the set of biomarkers and the data associated with a physical state of the surgeon to the surgical hub 20006 for further processing. One or more environmental sensing devices may send environmental information to the surgical hub 20006. For example, the environmental sensing devices may include a camera 20021 for detecting hand/body position of an HCP. The environmental sensing devices may include microphones 20022 for measuring the ambient noise in the surgical theater. Other environmental sensing devices may include devices, for example, a thermometer to measure temperature and a hygrometer to measure humidity of the surroundings in the surgical theater, etc. The surgical hub 20006, alone or in communication with the cloud computing system, may use the surgeon biomarker measurement data and/or environmental sensing information to modify the control algorithms of hand-held instruments or the averaging delay of a robotic interface, for example, to minimize tremors. In an example, the HCP sensing systems 20020 may measure one or more surgeon biomarkers associated with an HCP and send the measurement data associated with the surgeon biomarkers to the surgical hub 20006. The HCP sensing systems 20020 may use one or more of the following RF protocols for communicating with the surgical hub 20006: Bluetooth, Bluetooth Low-Energy (BLE), Bluetooth Smart, Zigbee, Z-wave, IPv6 Low-power wireless Personal Area Network (6LoWPAN), Wi-Fi. The surgeon biomarkers may include one or more of the following: stress, heart rate, etc. The environmental measurements from the surgical theater may include ambient noise level associated with the surgeon or the patient, surgeon and/or staff movements, surgeon and/or staff attention level, etc.

The surgical hub 20006 may use the surgeon biomarker measurement data associated with an HCP to adaptively control one or more surgical instruments 20031. For example, the surgical hub 20006 may send a control program to a surgical instrument 20031 to control its actuators to limit or compensate for fatigue and use of fine motor skills. The surgical hub 20006 may send the control program based on situational awareness and/or the context on importance or criticality of a task. The control program may instruct the instrument to alter operation to provide more control when control is needed.

FIG. 3 shows an example HCP monitoring system 20002 with a surgical hub 20006 paired with a wearable sensing system 20011, an environmental sensing system 20015, a human interface system 20012, a robotic system 20013, and an intelligent instrument 20014. The hub 20006 includes a display 20048, an imaging module 20049, a generator module 20050, a communication module 20056, a processor module 20057, a storage array 20058, and an operating-room mapping module 20059. In certain aspects, as illustrated in FIG. 3 , the hub 20006 further includes a smoke evacuation module 20054 and/or a suction/irrigation module 20055. During a surgical procedure, energy application to tissue, for sealing and/or cutting, is generally associated with smoke evacuation, suction of excess fluid, and/or irrigation of the tissue. Fluid, power, and/or data lines from different sources are often entangled during the surgical procedure. Valuable time can be lost addressing this issue during a surgical procedure. Detangling the lines may necessitate disconnecting the lines from their respective modules, which may require resetting the modules. The hub modular enclosure 20060 offers a unified environment for managing the power, data, and fluid lines, which reduces the frequency of entanglement between such lines. Aspects of the present disclosure present a surgical hub 20006 for use in a surgical procedure that involves energy application to tissue at a surgical site. The surgical hub 20006 includes a hub enclosure 20060 and a combo generator module slidably receivable in a docking station of the hub enclosure 20060. The docking station includes data and power contacts. The combo generator module includes two or more of an ultrasonic energy generator component, a bipolar RF energy generator component, and a monopolar RF energy generator component that are housed in a single unit. In one aspect, the combo generator module also includes a smoke evacuation component, at least one energy delivery cable for connecting the combo generator module to a surgical instrument, at least one smoke evacuation component configured to evacuate smoke, fluid, and/or particulates generated by the application of therapeutic energy to the tissue, and a fluid line extending from the remote surgical site to the smoke evacuation component. In one aspect, the fluid line may be a first fluid line, and a second fluid line may extend from the remote surgical site to a suction and irrigation module 20055 slidably received in the hub enclosure 20060. In one aspect, the hub enclosure 20060 may include a fluid interface. Certain surgical procedures may require the application of more than one energy type to the tissue. One energy type may be more beneficial for cutting the tissue, while another different energy type may be more beneficial for sealing the tissue. For example, a bipolar generator can be used to seal the tissue while an ultrasonic generator can be used to cut the sealed tissue. Aspects of the present disclosure present a solution where a hub modular enclosure 20060 is configured to accommodate different generators and facilitate an interactive communication therebetween. One of the advantages of the hub modular enclosure 20060 is enabling the quick removal and/or replacement of various modules. Aspects of the present disclosure present a modular surgical enclosure for use in a surgical procedure that involves energy application to tissue. The modular surgical enclosure includes a first energy-generator module, configured to generate a first energy for application to the tissue, and a first docking station comprising a first docking port that includes first data and power contacts, wherein the first energy-generator module is slidably movable into an electrical engagement with the power and data contacts and wherein the first energy-generator module is slidably movable out of the electrical engagement with the first power and data contacts. Further to the above, the modular surgical enclosure also includes a second energy-generator module configured to generate a second energy, different than the first energy, for application to the tissue, and a second docking station comprising a second docking port that includes second data and power contacts, wherein the second energy generator module is slidably movable into an electrical engagement with the power and data contacts, and wherein the second energy-generator module is slidably movable out of the electrical engagement with the second power and data contacts. In addition, the modular surgical enclosure also includes a communication bus between the first docking port and the second docking port, configured to facilitate communication between the first energy-generator module and the second energy-generator module. Referring to FIG. 3 , aspects of the present disclosure are presented for a hub modular enclosure 20060 that allows the modular integration of a generator module 20050, a smoke evacuation module 20054, and a suction/irrigation module 20055. The hub modular enclosure 20060 further facilitates interactive communication between the modules 20059, 20054, and 20055. The generator module 20050 can be a generator module 20050 with integrated monopolar, bipolar, and ultrasonic components supported in a single housing unit slidably insertable into the hub modular enclosure 20060. The generator module 20050 can be configured to connect to a monopolar device 20051, a bipolar device 20052, and an ultrasonic device 20053. Alternatively, the generator module 20050 may comprise a series of monopolar, bipolar, and/or ultrasonic generator modules that interact through the hub modular enclosure 20060. The hub modular enclosure 20060 can be configured to facilitate the insertion of multiple generators and interactive communication between the generators docked into the hub modular enclosure 20060 so that the generators would act as a single generator.

FIG. 4 illustrates a surgical data network having a set of communication hubs configured to connect a set of sensing systems, environment sensing system(s), and a set of other modular devices located in one or more operating theaters of a healthcare facility, a patient recovery room, or a room in a healthcare facility specially equipped for surgical operations, to the cloud, in accordance with at least one aspect of the present disclosure.

As illustrated in FIG. 4 , a surgical hub system 20060 may include a modular communication hub 20065 that is configured to connect modular devices located in a healthcare facility to a cloud-based system (e.g., a cloud computing system 20064 that may include a remote server 20067 coupled to a remote storage 20068). The modular communication hub 20065 and the devices may be connected in a room in a healthcare facility specially equipped for surgical operations. In one aspect, the modular communication hub 20065 may include a network hub 20061 and/or a network switch 20062 in communication with a network router 20066. The modular communication hub 20065 may be coupled to a local computer system 20063 to provide local computer processing and data manipulation.

The computer system 20063 may comprise a processor and a network interface 20100. The processor may be coupled to a communication module, storage, memory, non-volatile memory, and input/output (I/O) interface via a system bus. The system bus can be any of several types of bus structure(s) including the memory bus or memory controller, a peripheral bus or external bus, and or a local bus using any variety of available bus architectures including, but not limited to, 9-bit bus, Industrial Standard Architecture (ISA), Micro-Channel Architecture (MSA), Extended ISA (EISA), Intelligent Drive Electronics (IDE), VESA Local Bus (VLB), Peripheral Component Interconnect (PCI), USB, Advanced Graphics Port (AGP), Personal Computer Memory Card International Association bus (PCMCIA), Small Computer Systems Interface (SCSI), or any other proprietary bus.

The processor may be any single-core or multicore processor such as those known under the trade name ARM Cortex by Texas Instruments. In one aspect, the processor may be an LM4F230H5QR ARM Cortex-M4F Processor Core, available from Texas Instruments, for example, comprising an on-chip memory of 256 KB single-cycle flash memory, or other non-volatile memory, up to 40 MHz, a prefetch buffer to improve performance above 40 MHz, a 32 KB single-cycle serial random access memory (SRAM), an internal read-only memory (ROM) loaded with StellarisWare® software, a 2 KB electrically erasable programmable read-only memory (EEPROM), and/or one or more pulse width modulation (PWM) modules, one or more quadrature encoder inputs (QEI) analogs, one or more 12-bit analog-to-digital converters (ADCs) with 12 analog input channels, details of which are available for the product datasheet.

In an example, the processor may comprise a safety controller comprising two controller-based families such as TMS570 and RM4x, known under the trade name Hercules ARM Cortex R4, also by Texas Instruments. The safety controller may be configured specifically for IEC 61508 and ISO 26262 safety critical applications, among others, to provide advanced integrated safety features while delivering scalable performance, connectivity, and memory options.

It is to be appreciated that the computer system 20063 may include software that acts as an intermediary between users and the basic computer resources described in a suitable operating environment. Such software may include an operating system. The operating system, which can be stored on the disk storage, may act to control and allocate resources of the computer system. System applications may take advantage of the management of resources by the operating system through program modules and program data stored either in the system memory or on the disk storage. It is to be appreciated that various components described herein can be implemented with various operating systems or combinations of operating systems.

A user may enter commands or information into the computer system 20063 through input device(s) coupled to the I/O interface. The input devices may include, but are not limited to, a pointing device such as a mouse, trackball, stylus, touch pad, keyboard, microphone, joystick, game pad, satellite dish, scanner, TV tuner card, digital camera, digital video camera, web camera, and the like. These and other input devices connect to the processor 20102 through the system bus via interface port(s). The interface port(s) include, for example, a serial port, a parallel port, a game port, and a USB. The output device(s) use some of the same types of ports as input device(s). Thus, for example, a USB port may be used to provide input to the computer system 20063 and to output information from the computer system 20063 to an output device. An output adapter may be provided to illustrate that there can be some output devices like monitors, displays, speakers, and printers, among other output devices that may require special adapters. The output adapters may include, by way of illustration and not limitation, video and sound cards that provide a means of connection between the output device and the system bus. It should be noted that other devices and/or systems of devices, such as remote computer(s), may provide both input and output capabilities.

The computer system 20063 can operate in a networked environment using logical connections to one or more remote computers, such as cloud computer(s), or local computers. The remote cloud computer(s) can be a personal computer, server, router, network PC, workstation, microprocessor-based appliance, peer device, or other common network node, and the like, and typically includes many or all of the elements described relative to the computer system. For purposes of brevity, only a memory storage device is illustrated with the remote computer(s). The remote computer(s) may be logically connected to the computer system through a network interface and then physically connected via a communication connection. The network interface may encompass communication networks such as local area networks (LANs) and wide area networks (WANs). LAN technologies may include Fiber Distributed Data Interface (FDDI), Copper Distributed Data Interface (CDDI), Ethernet/IEEE 802.3, Token Ring/IEEE 802.5, and the like. WAN technologies may include, but are not limited to, point-to-point links, circuit-switching networks like Integrated Services Digital Networks (ISDN) and variations thereon, packet-switching networks, and Digital Subscriber Lines (DSL).

In various examples, the computer system 20063 may comprise an image processor, image-processing engine, media processor, or any specialized digital signal processor (DSP) used for the processing of digital images. The image processor may employ parallel computing with single instruction, multiple data (SIMD) or multiple instruction, multiple data (MIMD) technologies to increase speed and efficiency. The digital image-processing engine can perform a range of tasks. The image processor may be a system on a chip with multicore processor architecture.

The communication connection(s) may refer to the hardware/software employed to connect the network interface to the bus. While the communication connection is shown for illustrative clarity inside the computer system 20063, it can also be external to the computer system 20063. The hardware/software necessary for connection to the network interface may include, for illustrative purposes only, internal and external technologies such as modems, including regular telephone-grade modems, cable modems, optical fiber modems, and DSL modems, ISDN adapters, and Ethernet cards. In some examples, the network interface may also be provided using an RF interface.

Surgical data network associated with the surgical hub system 20060 may be configured as passive, intelligent, or switching. A passive surgical data network serves as a conduit for the data, enabling it to go from one device (or segment) to another and to the cloud computing resources. An intelligent surgical data network includes additional features to enable the traffic passing through the surgical data network to be monitored and to configure each port in the network hub 20061 or network switch 20062. An intelligent surgical data network may be referred to as a manageable hub or switch. A switching hub reads the destination address of each packet and then forwards the packet to the correct port.

Modular devices 1 a-1 n located in the operating theater may be coupled to the modular communication hub 20065. The network hub 20061 and/or the network switch 20062 may be coupled to a network router 20066 to connect the devices 1 a-1 n to the cloud computing system 20064 or the local computer system 20063. Data associated with the devices 1 a-1 n may be transferred to cloud-based computers via the router for remote data processing and manipulation. Data associated with the devices 1 a-1 n may also be transferred to the local computer system 20063 for local data processing and manipulation. Modular devices 2 a-2 m located in the same operating theater also may be coupled to a network switch 20062. The network switch 20062 may be coupled to the network hub 20061 and/or the network router 20066 to connect the devices 2 a-2 m to the cloud 20064. Data associated with the devices 2 a-2 m may be transferred to the cloud computing system 20064 via the network router 20066 for data processing and manipulation. Data associated with the devices 2 a-2 m may also be transferred to the local computer system 20063 for local data processing and manipulation.

The wearable sensing system 20011 may include one or more sensing systems 20069. The sensing systems 20069 may include an HCP sensing system and/or a patient sensing system. The one or more sensing systems 20069 may be in communication with the computer system 20063 of a surgical hub system 20060 or the cloud server 20067 directly via one of the network routers 20066 or via a network hub 20061 or network switching 20062 that is in communication with the network routers 20066.

The sensing systems 20069 may be coupled to the network router 20066 to connect to the sensing systems 20069 to the local computer system 20063 and/or the cloud computing system 20064. Data associated with the sensing systems 20069 may be transferred to the cloud computing system 20064 via the network router 20066 for data processing and manipulation. Data associated with the sensing systems 20069 may also be transferred to the local computer system 20063 for local data processing and manipulation.

As illustrated in FIG. 4 , the surgical hub system 20060 may be expanded by interconnecting multiple network hubs 20061 and/or multiple network switches 20062 with multiple network routers 20066. The modular communication hub 20065 may be contained in a modular control tower configured to receive multiple devices 1 a-1 n/2 a-2 m. The local computer system 20063 also may be contained in a modular control tower. The modular communication hub 20065 may be connected to a display 20068 to display images obtained by some of the devices 1 a-1 n/2 a-2 m, for example during surgical procedures. In various aspects, the devices 1 a-1 n/2 a-2 m may include, for example, various modules such as an imaging module coupled to an endoscope, a generator module coupled to an energy-based surgical device, a smoke evacuation module, a suction/irrigation module, a communication module, a processor module, a storage array, a surgical device coupled to a display, and/or a non-contact sensor module, among other modular devices that may be connected to the modular communication hub 20065 of the surgical data network.

In one aspect, the surgical hub system 20060 illustrated in FIG. 4 may comprise a combination of network hub(s), network switch(es), and network router(s) connecting the devices 1 a-1 n/2 a-2 m or the sensing systems 20069 to the cloud-base system 20064. One or more of the devices 1 a-1 n/2 a-2 m or the sensing systems 20069 coupled to the network hub 20061 or network switch 20062 may collect data or measurement data in real-time and transfer the data to cloud computers for data processing and manipulation. It will be appreciated that cloud computing relies on sharing computing resources rather than having local servers or personal devices to handle software applications. The word “cloud” may be used as a metaphor for “the Internet,” although the term is not limited as such. Accordingly, the term “cloud computing” may be used herein to refer to “a type of Internet-based computing,” where different services-such as servers, storage, and applications—are delivered to the modular communication hub 20065 and/or computer system 20063 located in the surgical theater (e.g., a fixed, mobile, temporary, or field operating room or space) and to devices connected to the modular communication hub 20065 and/or computer system 20063 through the Internet. The cloud infrastructure may be maintained by a cloud service provider. In this context, the cloud service provider may be the entity that coordinates the usage and control of the devices 1 a-1 n/2 a-2 m located in one or more operating theaters. The cloud computing services can perform a large number of calculations based on the data gathered by smart surgical instruments, robots, sensing systems, and other computerized devices located in the operating theater. The hub hardware enables multiple devices, sensing systems, and/or connections to be connected to a computer that communicates with the cloud computing resources and storage.

Applying cloud computer data processing techniques on the data collected by the devices 1 a-1 n/2 a-2 m, the surgical data network can provide improved surgical outcomes, reduced costs, and improved patient satisfaction. At least some of the devices 1 a-1 n/2 a-2 m may be employed to view tissue states to assess leaks or perfusion of sealed tissue after a tissue sealing and cutting procedure. At least some of the devices 1 a-1 n/2 a-2 m may be employed to identify pathology, such as the effects of diseases, using the cloud-based computing to examine data including images of samples of body tissue for diagnostic purposes. This may include localization and margin confirmation of tissue and phenotypes. At least some of the devices 1 a-1 n/2 a-2 m may be employed to identify anatomical structures of the body using a variety of sensors integrated with imaging devices and techniques such as overlaying images captured by multiple imaging devices. The data gathered by the devices 1 a-1 n/2 a-2 m, including image data, may be transferred to the cloud computing system 20064 or the local computer system 20063 or both for data processing and manipulation including image processing and manipulation. The data may be analyzed to improve surgical procedure outcomes by determining if further treatment, such as the application of endoscopic intervention, emerging technologies, a targeted radiation, targeted intervention, and precise robotics to tissue-specific sites and conditions, may be pursued. Such data analysis may further employ outcome analytics processing and using standardized approaches may provide beneficial feedback to either confirm surgical treatments and the behavior of the surgeon or suggest modifications to surgical treatments and the behavior of the surgeon.

Applying cloud computer data processing techniques on the measurement data collected by the sensing systems 20069, the surgical data network can provide improved surgical outcomes, improved recovery outcomes, reduced costs, and improved patient satisfaction. At least some of the sensing systems 20069 may be employed to assess physiological conditions of a surgeon operating on a patient or a patient being prepared for a surgical procedure or a patient recovering after a surgical procedure. The cloud-based computing system 20064 may be used to monitor biomarkers associated with a surgeon or a patient in real-time and to generate surgical plans based at least on measurement data gathered prior to a surgical procedure, provide control signals to the surgical instruments during a surgical procedure, notify a patient of a complication during post-surgical period.

The operating theater devices 1 a-1 n may be connected to the modular communication hub 20065 over a wired channel or a wireless channel depending on the configuration of the devices 1 a-1 n to a network hub 20061. The network hub 20061 may be implemented, in one aspect, as a local network broadcast device that works on the physical layer of the Open System Interconnection (OSI) model. The network hub may provide connectivity to the devices 1 a-1 n located in the same operating theater network. The network hub 20061 may collect data in the form of packets and sends them to the router in half duplex mode. The network hub 20061 may not store any media access control/Internet Protocol (MAC/IP) to transfer the device data. Only one of the devices 1 a-1 n can send data at a time through the network hub 20061. The network hub 20061 may not have routing tables or intelligence regarding where to send information and broadcasts all network data across each connection and to a remote server 20067 of the cloud computing system 20064. The network hub 20061 can detect basic network errors such as collisions but having all information broadcast to multiple ports can be a security risk and cause bottlenecks.

The operating theater devices 2 a-2 m may be connected to a network switch 20062 over a wired channel or a wireless channel. The network switch 20062 works in the data link layer of the OSI model. The network switch 20062 may be a multicast device for connecting the devices 2 a-2 m located in the same operating theater to the network. The network switch 20062 may send data in the form of frames to the network router 20066 and may work in full duplex mode. Multiple devices 2 a-2 m can send data at the same time through the network switch 20062. The network switch 20062 stores and uses MAC addresses of the devices 2 a-2 m to transfer data.

The network hub 20061 and/or the network switch 20062 may be coupled to the network router 20066 for connection to the cloud computing system 20064. The network router 20066 works in the network layer of the OSI model. The network router 20066 creates a route for transmitting data packets received from the network hub 20061 and/or network switch 20062 to cloud-based computer resources for further processing and manipulation of the data collected by any one of or all the devices 1 a-1 n/2 a-2 m and wearable sensing system 20011. The network router 20066 may be employed to connect two or more different networks located in different locations, such as, for example, different operating theaters of the same healthcare facility or different networks located in different operating theaters of different healthcare facilities. The network router 20066 may send data in the form of packets to the cloud computing system 20064 and works in full duplex mode. Multiple devices can send data at the same time. The network router 20066 may use IP addresses to transfer data.

In an example, the network hub 20061 may be implemented as a USB hub, which allows multiple USB devices to be connected to a host computer. The USB hub may expand a single USB port into several tiers so that there are more ports available to connect devices to the host system computer. The network hub 20061 may include wired or wireless capabilities to receive information over a wired channel or a wireless channel. In one aspect, a wireless USB short-range, high-bandwidth wireless radio communication protocol may be employed for communication between the devices 1 a-1 n and devices 2 a-2 m located in the operating theater.

In examples, the operating theater devices 1 a-1 n/2 a-2 m and/or the sensing systems 20069 may communicate to the modular communication hub 20065 via Bluetooth wireless technology standard for exchanging data over short distances (using short-wavelength UHF radio waves in the ISM band from 2.4 to 2.485 GHz) from fixed and mobile devices and building personal area networks (PANs). The operating theater devices 1 a-1 n/2 a-2 m and/or the sensing systems 20069 may communicate to the modular communication hub 20065 via a number of wireless or wired communication standards or protocols, including but not limited to Bluetooth, Low-Energy Bluetooth, near-field communication (NFC), Wi-Fi (IEEE 802.11 family), WiMAX (IEEE 802.16 family), IEEE 802.20, new radio (NR), long-term evolution (LTE), and Ev-DO, HSPA+, HSDPA+, HSUPA+, EDGE, GSM, GPRS, CDMA, TDMA, DECT, and Ethernet derivatives thereof, as well as any other wireless and wired protocols that are designated as 3G, 4G, 5G, and beyond. The computing module may include a plurality of communication modules. For instance, a first communication module may be dedicated to shorter-range wireless communications such as Wi-Fi and Bluetooth Low-Energy Bluetooth, Bluetooth Smart, and a second communication module may be dedicated to longer-range wireless communications such as GPS, EDGE, G PRS, CDMA, WiMAX, LTE, Ev-DO, HSPA+, HSDPA+, HSUPA+, EDGE, GSM, GPRS, CDMA, TDMA, and others.

The modular communication hub 20065 may serve as a central connection for one or more of the operating theater devices 1 a-1 n/2 a-2 m and/or the sensing systems 20069 and may handle a data type known as frames. Frames may carry the data generated by the devices 1 a-1 n/2 a-2 m and/or the sensing systems 20069. When a frame is received by the modular communication hub 20065, it may be amplified and/or sent to the network router 20066, which may transfer the data to the cloud computing system 20064 or the local computer system 20063 by using a number of wireless or wired communication standards or protocols, as described herein.

The modular communication hub 20065 can be used as a standalone device or be connected to compatible network hubs 20061 and network switches 20062 to form a larger network. The modular communication hub 20065 can be generally easy to install, configure, and maintain, making it a good option for networking the operating theater devices 1 a-1 n/2 a-2 m.

FIG. 5 illustrates a computer-implemented interactive surgical system 20070 that may be a part of the HCP monitoring system 20002. The computer-implemented interactive surgical system 20070 is similar in many respects to the HCP sensing system 20002. For example, the computer-implemented interactive surgical system 20070 may include one or more surgical sub-systems 20072, which are similar in many respects to the HCP monitoring systems 20002. Each sub-surgical system 20072 may include at least one surgical hub 20076 in communication with a cloud computing system 20064 that may include a remote server 20077 and a remote storage 20078. In one aspect, the computer-implemented interactive surgical system 20070 may include a modular control tower 20085 connected to multiple operating theater devices such as sensing systems 20001, intelligent surgical instruments, robots, and other computerized devices located in the operating theater.

As illustrated in the example of FIG. 5 , the modular control tower 20085 may be coupled to an imaging module 20088 that may be coupled to an endoscope 20087, a generator module 20090 that may be coupled to an energy device 20089, a smoke evacuator module 20091, a suction/irrigation module 20092, a communication module 20097, a processor module 20093, a storage array 20094, a smart device/instrument 20095 optionally coupled to a display 20086 and 20084 respectively, and a non-contact sensor module 20096. The non-contact sensor module 20096 may measure the dimensions of the operating theater and generate a map of the surgical theater using, ultrasonic, laser-type, and/or the like, non-contact measurement devices. Other distance sensors can be employed to determine the bounds of an operating room. An ultrasound-based non-contact sensor module may scan the operating theater by transmitting a burst of ultrasound and receiving the echo when it bounces off the perimeter walls of an operating theater as described under the heading “Surgical Hub Spatial Awareness Within an Operating Room” in U.S. Provisional Patent Application Ser. No. 62/611,341, titled INTERACTIVE SURGICAL PLATFORM, filed Dec. 28, 2017, which is herein incorporated by reference in its entirety. The sensor module may be configured to determine the size of the operating theater and to adjust Bluetooth-pairing distance limits. A laser-based non-contact sensor module may scan the operating theater by transmitting laser light pulses, receiving laser light pulses that bounce off the perimeter walls of the operating theater, and comparing the phase of the transmitted pulse to the received pulse to determine the size of the operating theater and to adjust Bluetooth pairing distance limits, for example.

The modular control tower 20085 may also be in communication with one or more sensing systems 20069 and an environmental sensing system 2015. The sensing systems 20069 may be connected to the modular control tower 20085 either directly via a router or via the communication module 20097. The operating theater devices may be coupled to cloud computing resources and data storage via the modular control tower 20085. A robot surgical hub 20082 also may be connected to the modular control tower 20085 and to the cloud computing resources. The devices/instruments 20095 or 20084, human interface system 20080, among others, may be coupled to the modular control tower 20085 via wired or wireless communication standards or protocols, as described herein. The human interface system 20080 may include a display sub-system and a notification sub-system. The modular control tower 20085 may be coupled to a hub display 20081 (e.g., monitor, screen) to display and overlay images received from the imaging module 20088, device/instrument display 20086, and/or other human interface systems 20080. The hub display 20081 also may display data received from devices connected to the modular control tower 20085 in conjunction with images and overlaid images.

FIG. 6 illustrates a logical diagram of a control system 20220 of a surgical instrument or a surgical tool in accordance with one or more aspects of the present disclosure. The surgical instrument or the surgical tool may be configurable. The surgical instrument may include surgical fixtures specific to the procedure at-hand, such as imaging devices, surgical staplers, energy devices, endocutter devices, or the like. For example, the surgical instrument may include any of a powered stapler, a powered stapler generator, an energy device, an advanced energy device, an advanced energy jaw device, an endocutter clamp, an energy device generator, an in-operating-room imaging system, a smoke evacuator, a suction-irrigation device, an insufflation system, or the like. The system 20220 may comprise a control circuit. The control circuit may include a microcontroller 20221 comprising a processor 20222 and a memory 20223. One or more of sensors 20225, 20226, 20227, for example, provide real-time feedback to the processor 20222. A motor 20230, driven by a motor driver 20229, operably couples a longitudinally movable displacement member to drive the I-beam knife element. A tracking system 20228 may be configured to determine the position of the longitudinally movable displacement member. The position information may be provided to the processor 20222, which can be programmed or configured to determine the position of the longitudinally movable drive member as well as the position of a firing member, firing bar, and I-beam knife element. Additional motors may be provided at the tool driver interface to control I-beam firing, closure tube travel, shaft rotation, and articulation. A display 20224 may display a variety of operating conditions of the instruments and may include touch screen functionality for data input. Information displayed on the display 20224 may be overlaid with images acquired via endoscopic imaging modules.

The microcontroller 20221 may be any single-core or multicore processor such as those known under the trade name ARM Cortex by Texas Instruments. In one aspect, the main microcontroller 20221 may be an LM4F230H5QR ARM Cortex-M4F Processor Core, available from Texas Instruments, for example, comprising an on-chip memory of 256 KB single-cycle flash memory, or other non-volatile memory, up to 40 MHz, a prefetch buffer to improve performance above 40 MHz, a 32 KB single-cycle SRAM, and internal ROM loaded with StellarisWare® software, a 2 KB EEPROM, one or more PWM modules, one or more QEI analogs, and/or one or more 12-bit ADCs with 12 analog input channels, details of which are available for the product datasheet.

The microcontroller 20221 may comprise a safety controller comprising two controller-based families such as TMS570 and RM4x, known under the trade name Hercules ARM Cortex R4, also by Texas Instruments. The safety controller may be configured specifically for IEC 61508 and ISO 26262 safety critical applications, among others, to provide advanced integrated safety features while delivering scalable performance, connectivity, and memory options.

The microcontroller 20221 may be programmed to perform various functions such as precise control over the speed and position of the knife and articulation systems. In one aspect, the microcontroller 20221 may include a processor 20222 and a memory 20223. The electric motor 20230 may be a brushed direct current (DC) motor with a gearbox and mechanical links to an articulation or knife system. In one aspect, a motor driver 20229 may be an A3941 available from Allegro Microsystems, Inc. Other motor drivers may be readily substituted for use in the tracking system 20228 comprising an absolute positioning system. A detailed description of an absolute positioning system is described in U.S. Patent Application Publication No. 2017/0296213, titled SYSTEMS AND METHODS FOR CONTROLLING A SURGICAL STAPLING AND CUTTING INSTRUMENT, which published on Oct. 19, 2017, which is herein incorporated by reference in its entirety.

The microcontroller 20221 may be programmed to provide precise control over the speed and position of displacement members and articulation systems. The microcontroller 20221 may be configured to compute a response in the software of the microcontroller 20221. The computed response may be compared to a measured response of the actual system to obtain an “observed” response, which is used for actual feedback decisions. The observed response may be a favorable, tuned value that balances the smooth, continuous nature of the simulated response with the measured response, which can detect outside influences on the system.

The motor 20230 may be controlled by the motor driver 20229 and can be employed by the firing system of the surgical instrument or tool. In various forms, the motor 20230 may be a brushed DC driving motor having a maximum rotational speed of approximately 25,000 RPM. In some examples, the motor 20230 may include a brushless motor, a cordless motor, a synchronous motor, a stepper motor, or any other suitable electric motor. The motor driver 20229 may comprise an H-bridge driver comprising field-effect transistors (FETs), for example. The motor 20230 can be powered by a power assembly releasably mounted to the handle assembly or tool housing for supplying control power to the surgical instrument or tool. The power assembly may comprise a battery which may include a number of battery cells connected in series that can be used as the power source to power the surgical instrument or tool. In certain circumstances, the battery cells of the power assembly may be replaceable and/or rechargeable. In at least one example, the battery cells can be lithium-ion batteries which can be couplable to and separable from the power assembly.

The motor driver 20229 may be an A3941 available from Allegro Microsystems, Inc. A3941 may be a full-bridge controller for use with external N-channel power metal-oxide semiconductor field-effect transistors (MOSFETs) specifically designed for inductive loads, such as brush DC motors. The driver 20229 may comprise a unique charge pump regulator that can provide full (>10 V) gate drive for battery voltages down to 7 V and can allow the A3941 to operate with a reduced gate drive, down to 5.5 V. A bootstrap capacitor may be employed to provide the above battery supply voltage required for N-channel MOSFETs. An internal charge pump for the high-side drive may allow DC (100% duty cycle) operation. The full bridge can be driven in fast or slow decay modes using diode or synchronous rectification. In the slow decay mode, current recirculation can be through the high-side or the low-side FETs. The power FETs may be protected from shoot-through by resistor-adjustable dead time. Integrated diagnostics provide indications of undervoltage, overtemperature, and power bridge faults and can be configured to protect the power MOSFETs under most short circuit conditions. Other motor drivers may be readily substituted for use in the tracking system 20228 comprising an absolute positioning system.

The tracking system 20228 may comprise a controlled motor drive circuit arrangement comprising a position sensor 20225 according to one aspect of this disclosure. The position sensor 20225 for an absolute positioning system may provide a unique position signal corresponding to the location of a displacement member. In some examples, the displacement member may represent a longitudinally movable drive member comprising a rack of drive teeth for meshing engagement with a corresponding drive gear of a gear reducer assembly. In some examples, the displacement member may represent the firing member, which could be adapted and configured to include a rack of drive teeth. In some examples, the displacement member may represent a firing bar or the I-beam, each of which can be adapted and configured to include a rack of drive teeth. Accordingly, as used herein, the term displacement member can be used generically to refer to any movable member of the surgical instrument or tool such as the drive member, the firing member, the firing bar, the I-beam, or any element that can be displaced. In one aspect, the longitudinally movable drive member can be coupled to the firing member, the firing bar, and the I-beam. Accordingly, the absolute positioning system can, in effect, track the linear displacement of the I-beam by tracking the linear displacement of the longitudinally movable drive member. In various aspects, the displacement member may be coupled to any position sensor 20225 suitable for measuring linear displacement. Thus, the longitudinally movable drive member, the firing member, the firing bar, or the I-beam, or combinations thereof, may be coupled to any suitable linear displacement sensor. Linear displacement sensors may include contact or non-contact displacement sensors. Linear displacement sensors may comprise linear variable differential transformers (LVDT), differential variable reluctance transducers (DVRT), a slide potentiometer, a magnetic sensing system comprising a movable magnet and a series of linearly arranged Hall effect sensors, a magnetic sensing system comprising a fixed magnet and a series of movable, linearly arranged Hall effect sensors, an optical sensing system comprising a movable light source and a series of linearly arranged photo diodes or photo detectors, an optical sensing system comprising a fixed light source and a series of movable linearly, arranged photodiodes or photodetectors, or any combination thereof.

The electric motor 20230 can include a rotatable shaft that operably interfaces with a gear assembly that is mounted in meshing engagement with a set, or rack, of drive teeth on the displacement member. A sensor element may be operably coupled to a gear assembly such that a single revolution of the position sensor 20225 element corresponds to some linear longitudinal translation of the displacement member. An arrangement of gearing and sensors can be connected to the linear actuator, via a rack and pinion arrangement, or a rotary actuator, via a spur gear or other connection. A power source may supply power to the absolute positioning system and an output indicator may display the output of the absolute positioning system. The displacement member may represent the longitudinally movable drive member comprising a rack of drive teeth formed thereon for meshing engagement with a corresponding drive gear of the gear reducer assembly. The displacement member may represent the longitudinally movable firing member, firing bar, I-beam, or combinations thereof.

A single revolution of the sensor element associated with the position sensor 20225 may be equivalent to a longitudinal linear displacement d1 of the of the displacement member, where d1 is the longitudinal linear distance that the displacement member moves from point “a” to point “b” after a single revolution of the sensor element coupled to the displacement member. The sensor arrangement may be connected via a gear reduction that results in the position sensor 20225 completing one or more revolutions for the full stroke of the displacement member. The position sensor 20225 may complete multiple revolutions for the full stroke of the displacement member.

A series of switches, where n is an integer greater than one, may be employed alone or in combination with a gear reduction to provide a unique position signal for more than one revolution of the position sensor 20225. The state of the switches may be fed back to the microcontroller 20221 that applies logic to determine a unique position signal corresponding to the longitudinal linear displacement d1+d2+ . . . dn of the displacement member. The output of the position sensor 20225 is provided to the microcontroller 20221. The position sensor 20225 of the sensor arrangement may comprise a magnetic sensor, an analog rotary sensor like a potentiometer, or an array of analog Hall-effect elements, which output a unique combination of position signals or values.

The position sensor 20225 may comprise any number of magnetic sensing elements, such as, for example, magnetic sensors classified according to whether they measure the total magnetic field or the vector components of the magnetic field. The techniques used to produce both types of magnetic sensors may encompass many aspects of physics and electronics. The technologies used for magnetic field sensing may include search coil, fluxgate, optically pumped, nuclear precession, SQUID, Hall-effect, anisotropic magnetoresistance, giant magnetoresistance, magnetic tunnel junctions, giant magnetoimpedance, magnetostrictive/piezoelectric composites, magnetodiode, magnetotransistor, fiber-optic, magneto-optic, and microelectromechanical systems-based magnetic sensors, among others.

The position sensor 20225 for the tracking system 20228 comprising an absolute positioning system may comprise a magnetic rotary absolute positioning system. The position sensor 20225 may be implemented as an AS5055EQFT single-chip magnetic rotary position sensor available from Austria Microsystems, AG. The position sensor 20225 is interfaced with the microcontroller 20221 to provide an absolute positioning system. The position sensor 20225 may be a low-voltage and low-power component and may include four Hall-effect elements in an area of the position sensor 20225 that may be located above a magnet. A high-resolution ADC and a smart power management controller may also be provided on the chip. A coordinate rotation digital computer (CORDIC) processor, also known as the digit-by-digit method and Volder's algorithm, may be provided to implement a simple and efficient algorithm to calculate hyperbolic and trigonometric functions that require only addition, subtraction, bit-shift, and table lookup operations. The angle position, alarm bits, and magnetic field information may be transmitted over a standard serial communication interface, such as a serial peripheral interface (SPI) interface, to the microcontroller 20221. The position sensor 20225 may provide 12 or 14 bits of resolution. The position sensor 20225 may be an AS5055 chip provided in a small QFN 16-pin 4×4×0.85 mm package.

The tracking system 20228 comprising an absolute positioning system may comprise and/or be programmed to implement a feedback controller, such as a PID, state feedback, and adaptive controller. A power source converts the signal from the feedback controller into a physical input to the system: in this case the voltage. Other examples include a PWM of the voltage, current, and force. Other sensor(s) may be provided to measure physical parameters of the physical system in addition to the position measured by the position sensor 20225. In some aspects, the other sensor(s) can include sensor arrangements such as those described in U.S. Pat. No. 9,345,481, titled STAPLE CARTRIDGE TISSUE THICKNESS SENSOR SYSTEM, which issued on May 24, 2016, which is herein incorporated by reference in its entirety; U.S. Patent Application Publication No. 2014/0263552, titled STAPLE CARTRIDGE TISSUE THICKNESS SENSOR SYSTEM, which published on Sep. 18, 2014, which is herein incorporated by reference in its entirety; and U.S. patent application Ser. No. 15/628,175, titled TECHNIQUES FOR ADAPTIVE CONTROL OF MOTOR VELOCITY OF A SURGICAL STAPLING AND CUTTING INSTRUMENT, filed Jun. 20, 2017, which is herein incorporated by reference in its entirety. In a digital signal processing system, an absolute positioning system is coupled to a digital data acquisition system where the output of the absolute positioning system will have a finite resolution and sampling frequency. The absolute positioning system may comprise a compare-and-combine circuit to combine a computed response with a measured response using algorithms, such as a weighted average and a theoretical control loop, that drive the computed response towards the measured response. The computed response of the physical system may take into account properties like mass, inertia, viscous friction, inductance resistance, etc., to predict what the states and outputs of the physical system will be by knowing the input.

The absolute positioning system may provide an absolute position of the displacement member upon power-up of the instrument, without retracting or advancing the displacement member to a reset (zero or home) position as may be required with conventional rotary encoders that merely count the number of steps forwards or backwards that the motor 20230 has taken to infer the position of a device actuator, drive bar, knife, or the like.

A sensor 20226, such as, for example, a strain gauge or a micro-strain gauge, may be configured to measure one or more parameters of the end effector, such as, for example, the amplitude of the strain exerted on the anvil during a clamping operation, which can be indicative of the closure forces applied to the anvil. The measured strain may be converted to a digital signal and provided to the processor 20222. Alternatively, or in addition to the sensor 20226, a sensor 20227, such as, for example, a load sensor, can measure the closure force applied by the closure drive system to the anvil. The sensor 20227, such as, for example, a load sensor, can measure the firing force applied to an I-beam in a firing stroke of the surgical instrument or tool. The I-beam is configured to engage a wedge sled, which is configured to upwardly cam staple drivers to force out staples into deforming contact with an anvil. The I-beam also may include a sharpened cutting edge that can be used to sever tissue as the I-beam is advanced distally by the firing bar. Alternatively, a current sensor 20231 can be employed to measure the current drawn by the motor 20230. The force required to advance the firing member can correspond to the current drawn by the motor 20230, for example. The measured force may be converted to a digital signal and provided to the processor 20222.

For example, the strain gauge sensor 20226 can be used to measure the force applied to the tissue by the end effector. A strain gauge can be coupled to the end effector to measure the force on the tissue being treated by the end effector. A system for measuring forces applied to the tissue grasped by the end effector may comprise a strain gauge sensor 20226, such as, for example, a micro-strain gauge, that can be configured to measure one or more parameters of the end effector, for example. In one aspect, the strain gauge sensor 20226 can measure the amplitude or magnitude of the strain exerted on a jaw member of an end effector during a clamping operation, which can be indicative of the tissue compression. The measured strain can be converted to a digital signal and provided to a processor 20222 of the microcontroller 20221. A load sensor 20227 can measure the force used to operate the knife element, for example, to cut the tissue captured between the anvil and the staple cartridge. A magnetic field sensor can be employed to measure the thickness of the captured tissue. The measurement of the magnetic field sensor also may be converted to a digital signal and provided to the processor 20222.

The measurements of the tissue compression, the tissue thickness, and/or the force required to close the end effector on the tissue, as respectively measured by the sensors 20226, 20227, can be used by the microcontroller 20221 to characterize the selected position of the firing member and/or the corresponding value of the speed of the firing member. In one instance, a memory 20223 may store a technique, an equation, and/or a lookup table which can be employed by the microcontroller 20221 in the assessment.

The control system 20220 of the surgical instrument or tool also may comprise wired or wireless communication circuits to communicate with the modular communication hub 20065 as shown in FIG. 5 .

FIG. 7 shows an example sensing system 20069. The sensing system may be an HCP sensing system or a patient sensing system. The sensing system 20069 may include a sensor unit 20235 and a human interface system 20242 that are in communication with a data processing and communication unit 20236. The data processing and communication unit 20236 may include an analog-to-digital converted 20237, a data processing unit 20238, a storage unit 20239, and an input/output interface 20241, a transceiver 20240. The sensing system 20069 may be in communication with a surgical hub or a computing device 20243, which in turn is in communication with a cloud computing system 20244. The cloud computing system 20244 may include a cloud storage system 20078 and one or more cloud servers 20077.

The sensor unit 20235 may include one or more ex vivo or in vivo sensors for measuring one or more biomarkers. The biomarkers may include, for example, blood pH, hydration state, oxygen saturation, core body temperature, heart rate, heart rate variability, sweat rate, skin conductance, blood pressure, light exposure, environmental temperature, respiratory rate, coughing and sneezing, gastrointestinal motility, gastrointestinal tract imaging, tissue perfusion pressure, bacteria in respiratory tract, alcohol consumption, lactate (sweat), peripheral temperature, positivity and optimism, adrenaline (sweat), cortisol (sweat), edema, mycotoxins, VO2 max, pre-operative pain, chemicals in the air, circulating tumor cells, stress and anxiety, confusion and delirium, physical activity, autonomic tone, circadian rhythm, menstrual cycle, sleep, etc. These biomarkers may be measured using one or more sensors, for example, photosensors (e.g., photodiodes, photoresistors), mechanical sensors (e.g., motion sensors), acoustic sensors, electrical sensors, electrochemical sensors, thermoelectric sensors, infrared sensors, etc. The sensors may measure the biomarkers as described herein using one of more of the following sensing technologies: photoplethysmography, electrocardiography, electroencephalography, colorimetry, impedimentary, potentiometry, amperometry, etc.

As illustrated in FIG. 7 , a sensor in the sensor unit 20235 may measure a physiological signal (e.g., a voltage, a current, a PPG signal, etc.) associated with a biomarker to be measured. The physiological signal to be measured may depend on the sensing technology used, as described herein. The sensor unit 20235 of the sensing system 20069 may be in communication with the data processing and communication unit 20236. In an example, the sensor unit 20235 may communicate with the data processing and communication unit 20236 using a wireless interface. The data processing and communication unit 20236 may include an analog-to-digital converter (ADC) 20237, a data processing unit 20238, a storage 20239, an I/O interface 20241, and an RF transceiver 20240. The data processing unit 20238 may include a processor and a memory unit.

The sensor unit 20235 may transmit the measured physiological signal to the ADC 20237 of the data processing and communication unit 20236. In an example, the measured physiological signal may be passed through one or more filters (e.g., an RC low-pass filter) before being sent to the ADC. The ADC may convert the measured physiological signal into measurement data associated with the biomarker. The ADC may pass measurement data to the data processing unit 20238 for processing. In an example, the data processing unit 20238 may send the measurement data associated with the biomarker to a surgical hub or a computing device 20243, which in turn may send the measurement data to a cloud computing system 20244 for further processing. The data processing unit may send the measurement data to the surgical hub or the computing device 20243 using one of the wireless protocols, as described herein. In an example, the data processing unit 20238 may first process the raw measurement data received from the sensor unit and send the processed measurement data to the surgical hub or a computing device 20243.

In an example, the data processing and communication unit 20236 of the sensing system 20069 may receive a threshold value associated with a biomarker for monitoring from a surgical hub, a computing device 20243, or directly from a cloud server 20077 of the cloud computing system 20244. The data processing unit 20236 may compare the measurement data associated with the biomarker to be monitored with the corresponding threshold value received from the surgical hub, the computing device 20243, or the cloud server 20077. The data processing and communication unit 20236 may send a notification message to the HID 20242 indicating that a measurement data value has crossed the threshold value. The notification message may include the measurement data associated with the monitored biomarker. The data processing and computing unit 20236 may send a notification via a transmission to a surgical hub or a computing device 20243 using one of the following RF protocols: Bluetooth, Bluetooth Low-Energy (BLE), Bluetooth Smart, Zigbee, Z-wave, IPv6 Low-power wireless Personal Area Network (6LoWPAN), Wi-Fi. The data processing unit 20238 may send a notification (e.g., a notification for an HCP) directly to a cloud server via a transmission to a cellular transmission/reception point (TRP) or a base station using one or more of the following cellular protocols: GSM/GPRS/EDGE (2G), UMTS/HSPA (3G), long term evolution (LTE) or 4G, LTE-Advanced (LTE-A), new radio (NR) or 5G. In an example, the sensing unit may be in communication with the hub/computing device via a router.

In an example, the sensor unit may include a sensor and an analog-to-digital converted (ADC). The ADC in the sensor unit may convert a physiological signal measured by the sensor into measurement data associated with a biomarker. The sensor unit may send the measurement data to the data processing and communication unit for further processing. In an example, the sensor unit may send the measurement data to the data processing and communication unit using an inter-integrated circuit (I2C) interface.

The data processing and communication unit includes a data processing unit, a storage unit, and an RF transceiver. The sensing system may be in communication with a surgical hub or a computing device, which in turn may be in communication with a cloud computing system 20244. The cloud computing system 20244 may include a remote server 20077 and an associated remote storage 20078. The sensor unit may include one or more ex vivo or in vivo sensors for measuring one or more biomarkers, as described herein.

The data processing and communication unit after processing the measurement data received from the sensor unit may further process the measurement data and/or send the measurement data to the smart hub or the computing device 20243. In an example, the data processing and communication unit may send the measurement data received from the sensor unit to the remote server 20077 of the cloud computing system 20244 for further processing and/or monitoring.

In an example, the sensor unit may include multiple sensors to measure one or more physiological signals associated with a patient or surgeon's biomarkers and/or one or more physical state signals associated with physical state of a person. A list of biomarkers may include biomarkers such as those biomarkers disclosed herein. The ADC(s) in the sensor unit may convert each of the physiological signals and/or physical state signals measured by the multiple sensors into respective measurement data. The sensor unit may send the measurement data associated with one or more biomarkers as well as the physical state of the person being monitored to the data processing and communication unit for further processing. The sensor unit may send the measurement data to the data processing and communication unit individually for each of the sensors or combined for all the sensors. In an example, the sensor unit may send the measurement data to the data processing and communication unit via an I2C interface.

FIG. 8 is an example of using a surgical task situational awareness and measurement data from one or more HCP sensing systems to adjust surgical instrument controls. FIG. 8 illustrates a timeline 20265 of an illustrative surgical procedure and the contextual information that a surgical hub can derive from data received from one or more surgical devices, one or more HCP sensing systems, and/or one or more environmental sensing systems at each step in the surgical procedure. The devices that could be controlled by a surgical hub may include advanced energy devices, endocutter clamps, etc. The HCP sensing systems may include sensing systems for measuring one or more biomarkers associated with the surgeon, for example, heart rate, sweat composition, respiratory rate, etc. The environmental sensing system may include systems for measuring one or more of the environmental attributes, for example, cameras for detecting a surgeon's position/movements/breathing pattern, spatial microphones, for example to measure ambient noise in the surgical theater and/or the tone of voice of a healthcare provider, temperature/humidity of the surroundings, etc.

In the following description of the timeline 20265 illustrated in FIG. 8 , reference should also be made to FIG. 5 . FIG. 5 provides various components used in a surgical procedure. The timeline 20265 depicts the steps that may be taken individually and/or collectively by the nurses, surgeons, and other medical personnel during the course of an exemplary colorectal surgical procedure. In a colorectal surgical procedure, a situationally aware surgical hub 20076 may receive data from various data sources throughout the course of the surgical procedure, including data generated each time an HCP utilizes a modular device/instrument 20095 that is paired with the surgical hub 20076. The surgical hub 20076 may receive this data from the paired modular devices 20095. The surgical hub may receive measurement data from sensing systems 20069. The surgical hub may use the data from the modular device/instruments 20095 and/or measurement data from the sensing systems 20069 to continually derive inferences (i.e., contextual information) about an HCP's stress level and the ongoing procedure as new data is received, such that the stress level of the surgeon relative to the step of the procedure that is being performed is obtained. The situational awareness system of the surgical hub 20076 may perform one or more of the following: record data pertaining to the procedure for generating reports, verify the steps being taken by the medical personnel, provide data or prompts (e.g., via a display screen) that may be pertinent for the particular procedural step, adjust modular devices based on the context (e.g., activate monitors, adjust the FOV of the medical imaging device, change the energy level of an ultrasonic surgical instrument or RF electrosurgical instrument), or take any other such action described herein. In an example, these steps may be performed by a remote server 20077 of a cloud system 20064 and communicated with the surgical hub 20076.

As a first step (not shown in FIG. 8 for brevity), the hospital staff members may retrieve the patient's EMR from the hospital's EMR database. Based on select patient data in the EMR, the surgical hub 20076 may determine that the procedure to be performed is a colorectal procedure. The staff members may scan the incoming medical supplies for the procedure. The surgical hub 20076 may cross-reference the scanned supplies with a list of supplies that can be utilized in various types of procedures and confirms that the mix of supplies corresponds to a colorectal procedure. The surgical hub 20076 may pair each of the sensing systems 20069 worn by different HCPs.

Wise Once each of the devices is ready and pre-surgical preparation is complete, the surgical team may begin by making incisions and place trocars. The surgical team may perform access and prep by dissecting adhesions, if any, and identifying inferior mesenteric artery (IMA) branches. The surgical hub 20076 can infer that the surgeon is in the process of dissecting adhesions, at least based on the data it may receive from the RF or ultrasonic generator indicating that an energy instrument is being fired. The surgical hub 20076 may cross-reference the received data with the retrieved steps of the surgical procedure to determine that an energy instrument being fired at this point in the process (e.g., after the completion of the previously discussed steps of the procedure) corresponds to the dissection step.

After dissection, the HCP may proceed to the ligation step (e.g., indicated by A1) of the procedure. As illustrated in FIG. 8 , the HCP may begin by ligating the IMA. The surgical hub 20076 may infer that the surgeon is ligating arteries and veins because it may receive data from the advanced energy jaw device and/or the endocutter indicating that the instrument is being fired. The surgical hub may also receive measurement data from one of the HCP's sensing systems indicating higher stress level of the HCP (e.g., indicated by B1 mark on the time axis). For example, higher stress level may be indicated by change in the HCP's heart rate from a base value. The surgical hub 20076, like the prior step, may derive this inference by cross-referencing the receipt of data from the surgical stapling and cutting instrument with the retrieved steps in the process (e.g., as indicated by A2 and A3). The surgical hub 20076 may monitor the advance energy jaw trigger ratio and/or the endocutter clamp and firing speed during the high stress time periods. In an example, the surgical hub 20076 may send an assistance control signal to the advanced energy jaw device and/or the endocutter device to control the device in operation. The surgical hub may send the assistance signal based on the stress level of the HCP that is operating the surgical device and/or situational awareness known to the surgical hub. For example, the surgical hub 20076 may send control assistance signals to an advanced energy device or an endocutter clamp, as indicated in FIG. 8 by A2 and A3.

The HCP may proceed to the next step of freeing the upper sigmoid followed by freeing descending colon, rectum, and sigmoid. The surgical hub 20076 may continue to monitor the high stress markers of the HCP (e.g., as indicated by D1, E1a, E1b, F1). The surgical hub 20076 may send assistance signals to the advanced energy jaw device and/or the endocutter device during the high stress time periods, as illustrated in FIG. 8 .

After mobilizing the colon, the HCP may proceed with the segmentectomy portion of the procedure. For example, the surgical hub 20076 may infer that the HCP is transecting the bowel and sigmoid removal based on data from the surgical stapling and cutting instrument, including data from its cartridge. The cartridge data can correspond to the size or type of staple being fired by the instrument, for example. As different types of staples are utilized for different types of tissues, the cartridge data can thus indicate the type of tissue being stapled and/or transected. It should be noted that surgeons regularly switch back and forth between surgical stapling/cutting instruments and surgical energy (e.g., RF or ultrasonic) instruments depending upon the step in the procedure because different instruments are better adapted for particular tasks. Therefore, the sequence in which the stapling/cutting instruments and surgical energy instruments are used can indicate what step of the procedure the surgeon is performing.

The surgical hub may determine and send a control signal to surgical device based on the stress level of the HCP. For example, during time period G1b, a control signal G2b may be sent to an endocutter clamp. Upon removal of the sigmoid, the incisions are closed, and the post-operative portion of the procedure may begin. The patient's anesthesia can be reversed. The surgical hub 20076 may infer that the patient is emerging from the anesthesia based on one or more sensing systems attached to the patient.

FIG. 9 shows an example computer-implemented interactive surgical system may be configured to monitor HCP biomarkers using one or more sensing systems 20001. The computer-implemented interactive surgical system may be configured to monitor HCP biomarkers using one or more sensing systems 20069. The HCP biomarkers and/or the patient biomarkers may be measured before, after, and/or during a surgical procedure. In one aspect, the computer-implemented interactive surgical system may be configured to monitor and analyze data related to the operation of various surgical systems 20069 that include surgical hubs, surgical instruments, robotic devices and operating theaters or healthcare facilities. The computer-implemented interactive surgical system may include a cloud-based analytics system. The computer-implemented interactive surgical system may include a local analytics system. The cloud-based analytics system may include one or more analytics servers.

A monitoring and analytics system may include a plurality of sensing systems 20268 (may be the same or similar to the sensing systems 20069), surgical instruments 20266 (may be the same or similar to instruments 20031), and/or a plurality of surgical hubs 20270 (may be the same or similar to hubs 20006). A surgical data network 20269 (may be the same or similar to the surgical data network described in FIG. 4 ) may couple the surgical hubs 20270 to the computing system 20271 (may be a local computing system, an edge computing system, or may be a cloud computing system such as cloud computing system 20064). The surgical hubs 20270 may be communicatively coupled to one or more surgical instruments 20266. The surgical hubs 20270 may also be communicatively coupled to the one or more sensing systems 20268, and the cloud 20271 of the computer-implemented interactive surgical system via the network 20269. The surgical hubs 20270 and the sensing systems 20268 may be communicatively coupled using wireless protocols as described herein. The computing system 20271 may be a local or remote centralized source of hardware and software for storing, processing, manipulating, and communicating measurement data from the sensing systems 20268 and data generated based on the operation of various surgical instruments 20266.

As shown in FIG. 9 , access to the computing system 20271 may be achieved via the network 20269. The network 20269 may be the Internet or some other suitable computer network. Surgical hubs 20270 that may be coupled to the computing system 20271 can be considered the client side of the computing system (e.g., cloud-based analytics system). Surgical instruments 20266 may be paired with the surgical hubs 20270 for control and implementation of various surgical procedures and/or operations, as described herein. Sensing systems 20268 may be paired with surgical hubs 20270 for in-surgical HCP monitoring of surgeon related biomarkers, pre-surgical HCP monitoring, monitoring, or post-surgical HCP monitoring. Environmental sensing systems 20267 may be paired with surgical hubs 20270 measuring environmental attributes associated with an HCP.

Surgical instruments 20266, environmental sensing systems 20267, and sensing systems 20268 may comprise wired or wireless transceivers for data transmission to and from their corresponding surgical hubs 20270 (which may also comprise transceivers). Combinations of one or more of surgical instruments 20266, sensing systems 20268, or surgical hubs 20270 may indicate particular locations, such as operating theaters, intensive care unit (ICU) rooms, or recovery rooms in healthcare facilities (e.g., hospitals), for providing medical operations, pre-surgical preparation, and/or post-surgical recovery. For example, the memory of a surgical hub 20270 may store location data.

As shown in FIG. 9 , the computing system 20271 may include one or more central servers 20272 (may be same or similar to remote server 20067), surgical hub application servers 20276, data analytics modules 20277, and an input/output (“I/O”) interface 20278. The central servers 20272 of the computing system 20271 may collectively administer the cloud computing system, which includes monitoring requests by client surgical hubs 20270 and managing the processing capacity of the computing system 20271 for executing the requests. Each of the central servers 20272 may comprise one or more processors 20273 coupled to suitable memory devices 20274 which can include volatile memory such as random-access memory (RAM) and non-volatile memory such as magnetic storage devices. The memory devices 20274 may comprise machine executable instructions that when executed cause the processors 20273 to execute the data analytics modules 20277 for the cloud-based data analysis, real-time monitoring of measurement data received from the sensing systems 20268, operations, recommendations, and other operations as described herein. The processors 20273 can execute the data analytics modules 20277 independently or in conjunction with hub applications independently executed by the hubs 20270. The central servers 20272 also may include aggregated medical data databases 20275, which can reside in the memory 20274.

Based on connections to various surgical hubs 20270 via the network 20269, the computing system 20271 can aggregate data from specific data generated by various surgical instruments 20266, real-time data from sensing systems 20268, and/or the surgical hubs 20270. Such aggregated data may be stored within the aggregated medical databases 20275 associated with the computing system 20271. The computing system 20271 may track real-time measurement data from the sensing systems 20268 and/or perform data analysis and operations on the measurement data and/or the aggregated data to yield insights and/or perform functions that individual hubs 20270 could not achieve on their own.

As shown in FIG. 9 , the computing system 20271 and the surgical hubs 20270 may be communicatively coupled to send and receive information. The I/O interface 20278 is connected to the plurality of surgical hubs 20270 via the network 20269. The I/O interface 20278 can be configured to transfer information between the surgical hubs 20270 and the aggregated medical data databases 20275. The I/O interface 20278 may facilitate read/write operations of the cloud-based analytics system. Such read/write operations may be executed in response to requests from hubs 20270. These requests could be transmitted to the surgical hubs 20270 through the hub applications. The I/O interface 20278 may include one or more high speed data ports, which may include universal serial bus (USB) ports, IEEE 1394 ports, as well as Wi-Fi and Bluetooth I/O interfaces for connecting the computing system 20271 to surgical hubs 20270. The hub application servers 20276 of the computing system 20271 may be configured to host and supply shared capabilities to software applications (e.g., hub applications) executed by surgical hubs 20270. For example, the hub application servers 20276 may manage requests made by the hub applications through the hubs 20270, control access to the aggregated medical data databases 20275, and perform load balancing.

The computing system may address various issues arising in the context of medical operations (e.g., pre-surgical monitoring, in-surgical monitoring, and post-surgical monitoring) and procedures performed using medical devices, such as the surgical instruments 20266, 20031. The surgical instruments 20266 may be digital surgical devices configured to interact with the computing system 20271 for implementing techniques to improve the performance of surgical operations. The computing system may address various issues arising in the context of monitoring one or more biomarkers associated with HCP(s) or a patient in pre-surgical, in-surgical, and post-surgical procedures using sensing systems 20268. Sensing systems 20268 may interact with the surgical hub 20270 and/or with the computing system 20271 for implementing techniques to monitor surgeon biomarkers and/or patient biomarkers. The sensing systems 20268 may include systems with one or more sensors that are configured to measure one or more biomarkers associated with an HCP participating in a medical operation and/or a patient on whom a medical operation is planned to be performed, is being performed or has been performed. Various surgical instruments 20266, sensing systems 20268, and/or surgical hubs 20270 may include human interface systems (e.g., having a touch-controlled user interfaces) such that HCPS and/or patients may control aspects of interaction between the surgical instruments 20266 or the sensing system 20268 and the computing system 20271. Other suitable user interfaces for control such as auditory controlled user interfaces may also be used.

FIG. 10 illustrates an example surgical system 20280 in accordance with the present disclosure and may include a surgical instrument 20282 that can be in communication with a console 20294 or a portable device 20296 through a local area network 20292 and/or a cloud network 20293 via a wired and/or wireless connection. The console 20294 and the portable device 20296 may be any suitable computing device. The surgical instrument 20282 may include a handle 20297, an adapter 20285, and a loading unit 20287. The adapter 20285 releasably couples to the handle 20297 and the loading unit 20287 releasably couples to the adapter 20285 such that the adapter 20285 transmits a force from a drive shaft to the loading unit 20287. The adapter 20285 or the loading unit 20287 may include a force gauge (not explicitly shown) disposed therein to measure a force exerted on the loading unit 20287. The loading unit 20287 may include an end effector 20289 having a first jaw 20291 and a second jaw 20290. The loading unit 20287 may be an in-situ loaded or multi-firing loading unit (MFLU) that allows a clinician to fire a plurality of fasteners multiple times without requiring the loading unit 20287 to be removed from a surgical site to reload the loading unit 20287.

The first and second jaws 20291, 20290 may be configured to clamp tissue therebetween, fire fasteners through the clamped tissue, and sever the clamped tissue. The first jaw 20291 may be configured to fire at least one fastener a plurality of times or may be configured to include a replaceable multi-fire fastener cartridge including a plurality of fasteners (e.g., staples, clips, etc.) that may be fired more than one time prior to being replaced. The second jaw 20290 may include an anvil that deforms or otherwise secures the fasteners, as the fasteners are ejected from the multi-fire fastener cartridge.

The handle 20297 may include a motor that is coupled to the drive shaft to affect rotation of the drive shaft. The handle 20297 may include a control interface to selectively activate the motor. The control interface may include buttons, switches, levers, sliders, touchscreen, and any other suitable input mechanisms or user interfaces, which can be engaged by a clinician to activate the motor.

The control interface of the handle 20297 may be in communication with a controller 20298 of the handle 20297 to selectively activate the motor to affect rotation of the drive shafts. The controller 20298 may be disposed within the handle 20297 and may be configured to receive input from the control interface and adapter data from the adapter 20285 or loading unit data from the loading unit 20287. The controller 20298 may analyze the input from the control interface and the data received from the adapter 20285 and/or loading unit 20287 to selectively activate the motor. The handle 20297 may also include a display that is viewable by a clinician during use of the handle 20297. The display may be configured to display portions of the adapter or loading unit data before, during, or after firing of the instrument 20282.

The adapter 20285 may include an adapter identification device 20284 disposed therein and the loading unit 20287 may include a loading unit identification device 20288 disposed therein. The adapter identification device 20284 may be in communication with the controller 20298, and the loading unit identification device 20288 may be in communication with the controller 20298. It will be appreciated that the loading unit identification device 20288 may be in communication with the adapter identification device 20284, which relays or passes communication from the loading unit identification device 20288 to the controller 20298.

The adapter 20285 may also include a plurality of sensors 20286 (one shown) disposed thereabout to detect various conditions of the adapter 20285 or of the environment (e.g., if the adapter 20285 is connected to a loading unit, if the adapter 20285 is connected to a handle, if the drive shafts are rotating, the torque of the drive shafts, the strain of the drive shafts, the temperature within the adapter 20285, a number of firings of the adapter 20285, a peak force of the adapter 20285 during firing, a total amount of force applied to the adapter 20285, a peak retraction force of the adapter 20285, a number of pauses of the adapter 20285 during firing, etc.). The plurality of sensors 20286 may provide an input to the adapter identification device 20284 in the form of data signals. The data signals of the plurality of sensors 20286 may be stored within or be used to update the adapter data stored within the adapter identification device 20284. The data signals of the plurality of sensors 20286 may be analog or digital. The plurality of sensors 20286 may include a force gauge to measure a force exerted on the loading unit 20287 during firing.

The handle 20297 and the adapter 20285 can be configured to interconnect the adapter identification device 20284 and the loading unit identification device 20288 with the controller 20298 via an electrical interface. The electrical interface may be a direct electrical interface (i.e., include electrical contacts that engage one another to transmit energy and signals therebetween). Additionally, or alternatively, the electrical interface may be a non-contact electrical interface to wirelessly transmit energy and signals therebetween (e.g., inductively transfer). It is also contemplated that the adapter identification device 20284 and the controller 20298 may be in wireless communication with one another via a wireless connection separate from the electrical interface.

The handle 20297 may include a transceiver 20283 that is configured to transmit instrument data from the controller 20298 to other components of the system 20280 (e.g., the LAN 20292, the cloud 20293, the console 20294, or the portable device 20296). The controller 20298 may also transmit instrument data and/or measurement data associated with one or more sensors 20286 to a surgical hub 20270, as illustrated in FIG. 9 . The transceiver 20283 may receive data (e.g., cartridge data, loading unit data, adapter data, or other notifications) from the surgical hub 20270. The transceiver 20283 may receive data (e.g., cartridge data, loading unit data, or adapter data) from the other components of the system 20280. For example, the controller 20298 may transmit instrument data including a serial number of an attached adapter (e.g., adapter 20285) attached to the handle 20297, a serial number of a loading unit (e.g., loading unit 20287) attached to the adapter 20285, and a serial number of a multi-fire fastener cartridge loaded into the loading unit to the console 20294. Thereafter, the console 20294 may transmit data (e.g., cartridge data, loading unit data, or adapter data) associated with the attached cartridge, loading unit, and adapter, respectively, back to the controller 20298. The controller 20298 can display messages on the local instrument display or transmit the message, via transceiver 20283, to the console 20294 or the portable device 20296 to display the message on the display 20295 or portable device screen, respectively.

FIG. 11 illustrates a diagram of a situationally aware surgical system 5100, in accordance with at least one aspect of the present disclosure. The data sources 5126 may include, for example, the modular devices 5102 (which can include sensors configured to detect parameters associated with the patient, HCPs and environment and/or the modular device itself), databases 5122 (e.g., an EMR database containing patient records), and patient monitoring devices 5124 (e.g., a blood pressure (BP) monitor and an electrocardiography (EKG) monitor), HCP monitoring devices 35510, and/or environment monitoring devices 35512. The surgical hub 5104 can be configured to derive the contextual information pertaining to the surgical procedure from the data based upon, for example, the particular combination(s) of received data or the particular order in which the data is received from the data sources 5126. The contextual information inferred from the received data can include, for example, the type of surgical procedure being performed, the particular step of the surgical procedure that the surgeon is performing, the type of tissue being operated on, or the body cavity that is the subject of the procedure. This ability by some aspects of the surgical hub 5104 to derive or infer information related to the surgical procedure from received data can be referred to as “situational awareness.” For example, the surgical hub 5104 can incorporate a situational awareness system, which is the hardware and/or programming associated with the surgical hub 5104 that derives contextual information pertaining to the surgical procedure from the received data.

The situational awareness system of the surgical hub 5104 can be configured to derive the contextual information from the data received from the data sources 5126 in a variety of different ways. For example, the situational awareness system can include a pattern recognition system, or machine learning system (e.g., an artificial neural network), that has been trained on training data to correlate various inputs (e.g., data from database(s) 5122, patient monitoring devices 5124, modular devices 5102, HCP monitoring devices 35510, and/or environment monitoring devices 35512) to corresponding contextual information regarding a surgical procedure. A machine learning system can be trained to accurately derive contextual information regarding a surgical procedure from the provided inputs. In examples, the situational awareness system can include a lookup table storing pre-characterized contextual information regarding a surgical procedure in association with one or more inputs (or ranges of inputs) corresponding to the contextual information. In response to a query with one or more inputs, the lookup table can return the corresponding contextual information for the situational awareness system for controlling the modular devices 5102. In examples, the contextual information received by the situational awareness system of the surgical hub 5104 can be associated with a particular control adjustment or set of control adjustments for one or more modular devices 5102. In examples, the situational awareness system can include a further machine learning system, lookup table, or other such system, which generates or retrieves one or more control adjustments for one or more modular devices 5102 when provided the contextual information as input.

A surgical hub 5104 incorporating a situational awareness system can provide a number of benefits for the surgical system 5100. One benefit may include improving the interpretation of sensed and collected data, which would in turn improve the processing accuracy and/or the usage of the data during the course of a surgical procedure. To return to a previous example, a situationally aware surgical hub 5104 could determine what type of tissue was being operated on; therefore, when an unexpectedly high force to close the surgical instrument's end effector is detected, the situationally aware surgical hub 5104 could correctly ramp up or ramp down the motor of the surgical instrument for the type of tissue.

The type of tissue being operated can affect the adjustments that are made to the compression rate and load thresholds of a surgical stapling and cutting instrument for a particular tissue gap measurement. A situationally aware surgical hub 5104 could infer whether a surgical procedure being performed is a thoracic or an abdominal procedure, allowing the surgical hub 5104 to determine whether the tissue clamped by an end effector of the surgical stapling and cutting instrument is lung (for a thoracic procedure) or stomach (for an abdominal procedure) tissue. The surgical hub 5104 could then adjust the compression rate and load thresholds of the surgical stapling and cutting instrument appropriately for the type of tissue.

The type of body cavity being operated in during an insufflation procedure can affect the function of a smoke evacuator. A situationally aware surgical hub 5104 could determine whether the surgical site is under pressure (by determining that the surgical procedure is utilizing insufflation) and determine the procedure type. As a procedure type can be generally performed in a specific body cavity, the surgical hub 5104 could then control the motor rate of the smoke evacuator appropriately for the body cavity being operated in. Thus, a situationally aware surgical hub 5104 could provide a consistent amount of smoke evacuation for both thoracic and abdominal procedures.

The type of procedure being performed can affect the optimal energy level for an ultrasonic surgical instrument or radio frequency (RF) electrosurgical instrument to operate at. Arthroscopic procedures, for example, may require higher energy levels because the end effector of the ultrasonic surgical instrument or RF electrosurgical instrument is immersed in fluid. A situationally aware surgical hub 5104 could determine whether the surgical procedure is an arthroscopic procedure. The surgical hub 5104 could then adjust the RF power level or the ultrasonic amplitude of the generator (e.g., “energy level”) to compensate for the fluid filled environment. Relatedly, the type of tissue being operated on can affect the optimal energy level for an ultrasonic surgical instrument or RF electrosurgical instrument to operate at. A situationally aware surgical hub 5104 could determine what type of surgical procedure is being performed and then customize the energy level for the ultrasonic surgical instrument or RF electrosurgical instrument, respectively, according to the expected tissue profile for the surgical procedure. Furthermore, a situationally aware surgical hub 5104 can be configured to adjust the energy level for the ultrasonic surgical instrument or RF electrosurgical instrument throughout the course of a surgical procedure, rather than just on a procedure-by-procedure basis. A situationally aware surgical hub 5104 could determine what step of the surgical procedure is being performed or will subsequently be performed and then update the control algorithms for the generator and/or ultrasonic surgical instrument or RF electrosurgical instrument to set the energy level at a value appropriate for the expected tissue type according to the surgical procedure step.

In examples, data can be drawn from additional data sources 5126 to improve the conclusions that the surgical hub 5104 draws from one data source 5126. A situationally aware surgical hub 5104 could augment data that it receives from the modular devices 5102 with contextual information that it has built up regarding the surgical procedure from other data sources 5126. For example, a situationally aware surgical hub 5104 can be configured to determine whether hemostasis has occurred (e.g., whether bleeding at a surgical site has stopped) according to video or image data received from a medical imaging device. The surgical hub 5104 can be further configured to compare a physiologic measurement (e.g., blood pressure sensed by a BP monitor communicably connected to the surgical hub 5104) with the visual or image data of hemostasis (e.g., from a medical imaging device communicably coupled to the surgical hub 5104) to make a determination on the integrity of the staple line or tissue weld. The situational awareness system of the surgical hub 5104 can consider the physiological measurement data to provide additional context in analyzing the visualization data. The additional context can be useful when the visualization data may be inconclusive or incomplete on its own.

For example, a situationally aware surgical hub 5104 could proactively activate the generator to which an RF electrosurgical instrument is connected if it determines that a subsequent step of the procedure requires the use of the instrument. Proactively activating the energy source can allow the instrument to be ready for use a soon as the preceding step of the procedure is completed.

The situationally aware surgical hub 5104 could determine whether the current or subsequent step of the surgical procedure requires a different view or degree of magnification on the display according to the feature(s) at the surgical site that the surgeon is expected to need to view. The surgical hub 5104 could proactively change the displayed view (supplied by, e.g., a medical imaging device for the visualization system 108) accordingly so that the display automatically adjusts throughout the surgical procedure.

The situationally aware surgical hub 5104 could determine which step of the surgical procedure is being performed or will subsequently be performed and whether particular data or comparisons between data will be required for that step of the surgical procedure. The surgical hub 5104 can be configured to automatically call up data screens based upon the step of the surgical procedure being performed, without waiting for the surgeon to ask for the particular information.

Errors may be checked during the setup of the surgical procedure or during the course of the surgical procedure. For example, the situationally aware surgical hub 5104 could determine whether the operating theater is setup properly or optimally for the surgical procedure to be performed. The surgical hub 5104 can be configured to determine the type of surgical procedure being performed, retrieve the corresponding checklists, product location, or setup needs (e.g., from a memory), and then compare the current operating theater layout to the standard layout for the type of surgical procedure that the surgical hub 5104 determines is being performed. In some exemplifications, the surgical hub 5104 can compare the list of items for the procedure and/or a list of devices paired with the surgical hub 5104 to a recommended or anticipated manifest of items and/or devices for the given surgical procedure. If there are any discontinuities between the lists, the surgical hub 5104 can provide an alert indicating that a particular modular device 5102, patient monitoring device 5124, HCP monitoring devices 35510, environment monitoring devices 35512, and/or other surgical item is missing. In some examples, the surgical hub 5104 can determine the relative distance or position of the modular devices 5102 and patient monitoring devices 5124 via proximity sensors, for example. The surgical hub 5104 can compare the relative positions of the devices to a recommended or anticipated layout for the particular surgical procedure. If there are any discontinuities between the layouts, the surgical hub 5104 can be configured to provide an alert indicating that the current layout for the surgical procedure deviates from the recommended layout.

The situationally aware surgical hub 5104 could determine whether the surgeon (or other HCP(s)) was making an error or otherwise deviating from the expected course of action during the course of a surgical procedure. For example, the surgical hub 5104 can be configured to determine the type of surgical procedure being performed, retrieve the corresponding list of steps or order of equipment usage (e.g., from a memory), and then compare the steps being performed or the equipment being used during the course of the surgical procedure to the expected steps or equipment for the type of surgical procedure that the surgical hub 5104 determined is being performed. The surgical hub 5104 can provide an alert indicating that an unexpected action is being performed or an unexpected device is being utilized at the particular step in the surgical procedure.

The surgical instruments (and other modular devices 5102) may be adjusted for the particular context of each surgical procedure (such as adjusting to different tissue types) and validating actions during a surgical procedure. Next steps, data, and display adjustments may be provided to surgical instruments (and other modular devices 5102) in the surgical theater according to the specific context of the procedure.

Object detection can be performed via computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, equipment, or objects) in digital images and videos. Object detection is used in computer vision tasks such as image annotation, activity recognition, face detection, face recognition, video object co-segmentation. Object detection is used in tracking objects, for example tracking a ball during a football match, tracking movement of a cricket bat, or tracking a person in a video. Object detection may be performed via neural network-based approach(es), and/or non-neural approaches. For example, features may be defined and classification may be performed based on the defined features, for example, via support vector machine (SVM). Neural techniques may perform object detection without specifically defining features, and may be based on convolutional neural networks (CNN).

Moving object detection may be performed to recognize the physical movement of a person or an object in a given place or region. By acting segmentation among moving objects and stationary area or region, the moving objects motion could be tracked and thus could be analyzed later. Moving object detection may be performed via background subtraction, frame differencing, temporal differencing, and or optical flow analysis.

Smart and self-identifying RF systems may be used to locate HCPs and equipment in the OR. HCPs, instruments, equipment and/or boundaries may be located using spatial identifying sensors. The locations of HCPs, equipment and/or boundaries may be tracked with respect to the room and/or with respect to the patient, via wireless sensors and beacons.

A wearable monitoring system may be coupled to a person, such as an HCP or a patient. Ultra-wide band monitoring may be performed to identify the location of the person within the OR, and/or the person's relative position to an equipment, a surgical instrument, another person, a boundary, and/or the like.

RF element identification and boundary monitoring may be performed. RF beacons may be placed on equipment or instruments. BLE beacons may be placed in physical CR's. For example, beacons may be placed in corners of the OR, outlining the boundaries of the room. BLE beacons may be place on structures, such as large structures within the OR. BLE beacons may be placed on device for monitoring the device location relative to one or more boundaries.

For example, RFID tags may be affixed onto instruments and/or HCPs. Electromagnetic gates may be placed in the OR to prevent or to minimize violation of boundaries.

Boundary violations may be detected by tracking beacon movements. For example, the surgical hub may detect a boundary violation upon determining that the beacon has moved across a boundary. If the boundary violation is associated with a device crossing a boundary, the surgical hub may deactivate the device and alert an HCP of change of status. If the boundary violation is a larger structure, an urgent message can be displayed to indicate the equipment is of concern.

RF beacons may be used to locate HCPS in the OR theater. The location of an HCP may be tracked via their identification badge. The identification badge may have an imbedded RF beacon. The RF beacon may be high frequency (HF) or ultra-high frequency (UHF). The read range may not be affected by fluids or the need to penetrate structures. Since the size of the OR's can vary, the HF or UHF can provide sufficient coverage to accommodate potential distance from the surgical hub.

A surgical instrument may be associated with a unique RFID identification. The location of the surgical instrument may be tracked. The current use and/or the previous history of the surgical instrument may be determined based on location tracking. An external reader from the surgical hub may be positioned around the patient. The external reader may be used to track surgical instruments that enter the OR field. A low frequency or an HF chip may be used on instruments. The low or high frequencies may enable the reader to penetrate body fluids.

Instrument use can be determined and tracked based on its location. For example, the number of times a surgical instrument has been used, the length of time a device was in the patient, and/or a level of security that the device had been through a sterilization cycle prior to being introduced into the OR may be determined via location tracking. Whether an instrument has been left in the patient may be detected via location tracking of the instrument.

OR room imaging may be performed by multiple sources via various technologies to determine HCP, instrument, and/or equipment locations and their aspects. More than one imaging device can be used through different energy types to locate objects and people within the OR, the walls of the OR, and/or their proximity. The location and/or proximity information may be used to identify and/or control their interactions. Instruments and/or equipment may be configured based on the identified interactions.

For example, ultrasonic echo location may be used to determine object motion and measurements of location. OR visual or multi-spectral imaging may be used to monitor user location, interaction, and communication. Audio monitoring may be used to determine and record noise generating monitoring and tracking.

Infrared (IR) thermographic monitoring may be used to monitor the core temperate and the changes of temperature of HCPs and patient to adjust systems, monitor for infection, and/or understand situational awareness. As an HCP enters into the OR, an IR signature may be created for the HCP. An initial IR association response may be logged, for example, via the surgical hub. During a procedure, if the stress levels of the HCP increases, the IR signature may display or register the increased stress levels.

The various imaging systems may be used in concert. For example, the surgical hub may be positioned in the OR. Once powered up, the surgical hub may use an ultrasonic echo to determine the OR boundaries (e.g., walls) and large equipment locations to map room. A grid map may be established with all required boundaries.

When an HCP enters into OR theater, the HCP may be identified as entering via a BLE beacon associated with HCP. The surgical hub may check the HCP into theater. The surgical hub may begin tracking the HCP via an optical camera. The IR camera may perform the initial scan of the identified HCP for base line stress level(s). Once procedure begins, the audio monitoring system may monitor and record sounds. The surgical hub may monitor for voice inflections and/or raised nervous voices. The audio monitoring system can be synchronized with the IR camera, for example, for verifying an increase in stress levels. This process may be performed for multiple HCPs.

The HCPs in the OR may be recognized and tracked via an ID badge having an RFID, NFC, and/or a wearable device. For example, as an HCP move in and out of a room, as they come close to another wearable device, as they come close to a surgical hub, the identity of the HCP may be determined. The surgical hub may request HCP identifying information from an RFID reader, NFC reader, or a wearable device, upon detecting an HCP entering the OR. The surgical hub may confirm the identity of an HCP based on other source(s) of information. The surgical hub may assume that the identity of the HCP associated with an ID badge or a wearable device until the ID badge or wearable device is off. Details related to identifying an HCP and/or a user role via a wearable device may be found in U.S. application Ser. No. 17/156,324, entitled ACTIVE RECOGNITION AND PAIRING SENSING SYSTEMS, which is herein incorporated by reference in its entirety.

The HCPs in the OR may be recognized and tracked via video processing from video captured by one or more cameras in the OR. Various known image or video processing technologies, such as keypoint detection and analysis, bounding box annotation, polygon mesh processing, image segmentation, facial recognition, gesture recognition, point cloud, lines and splines, and/or the like may be used to analyze the video feeds.

The location, movement, and/or orientation of various surgical products and instruments in the operating room may be identified and tracked. For example, a gyroscope or 3 axis accelerometers may be used to determine device orientation and position.

For example, a surgical instrument may be identified via one or more spatial registration markers located thereon. For example, visible fiducial markers could be placed on the instrument. The surgical hub may monitor the location, movement, and/or orientation of the surgical instrument via one or more camera in the OR. The fiducial marks may be in a predefined pattern. The surgical hub may associate a surgical instrument with particular fiducial mark(s) and may use the mark(s) to identify and model the instrument with the 3D computer environment it creates and records. The registration allows for the compensation for translation, rotation, scale, skew, and perspective. This may enable the surgical hub to detect and monitor the instruments even once a portion of the instrument is obscured.

For visible monitoring, camera calibration may be conducted when the system starts up. A predefined set of calibration markers within the hub camera view that may be fixed, such that the surgical hub may calibrate the camera for distance and focal length. The surgical hub may determine the exact length from itself to another calibration preset scale in the OR, and may use the measurement and the scale to calibrate the camera and focal distance. For example, the surgical hub may determine the exact distance via a measurement system. For example, measurement system(s) that employ laser Doppler, ultrasonic pinging, RF and/or other energy digital communication may be perform distance measurement and send the measurements to the surgical hub. The measurement system may be included in the surgical hub.

Distance may be inferred from active and/or passive electronic signal processing. For example, by monitoring the signal strength and compensating for emission power, emitting device antenna path, fight path, receiving device antenna path, and/or receiver sensitivity the communication between two paired systems or devices, the distance between the two systems or devices may be determined. For example, UHF or HF RFID tagged object may be tracked through a combination of predefined tag and distances in combination with unknown tags. The tags may be used to identify a product, device or instrument, and may allow the product, device or instrument tracked within the OR once identified. The tags may provide further information about the identified product, device or instrument. A RFID map may be generated from passive or active references tags with known locations (e.g., landmarks) to locate any unknown tag detected by the RFID reader antennas. The distances between the readers and the common detected tags may be measured using a large-scale path loss propagation model. The distance between the unknown tag and the detected landmarks (e.g., inter-tags distance) may be calculated.

A millimeter-wave radar may be used to track objects. Millimeter-wave radar may achieve an accuracy of around a few micrometers. With the radar operating using frequency-modulated continuous waves (FMCW), frequency and/and phase of radar beat signal may be used to determine the distance between the radar sensor and the object from which the radar signal is reflected.

A mapping or evaluation of the bounds of the operating room may be performed. For example, the surgical hub 20006 may maintain spatial awareness during operation by periodically mapping its operating room, which can be helpful in determining if the surgical hub 20006 has been moved. The reevaluation can be performed periodically or it can be triggered by an event such as observing a change in the devices of the HCP monitoring system 20002 that are deemed within the operating room. The change may be the detection of a new device that was not previously deemed as within the bounds of the operating room. The change may be a disappearance, disconnection, or un-pairing of a paired device that was previously deemed as residing within the operating room. The surgical hub 20006 may continuously monitor the connection with paired devices to detect the disappearance, disconnection, or un-pairing of a paired device.

An operating-room mapping module may contain a compass and integrated Bluetooth transceiver. Other communication mechanisms, which are not significantly affected by the hospital environment or geographical location, can be employed. Bluetooth Low Energy (BLE) beacon technology may achieve indoor distance measurements with accuracy of about 1-2 meters, with improved accuracy in closer proximities (within 0-6 meters). To improve the accuracy of the distance measurements, a compass is used with the BLE. The operating-room mapping module may the BLE and/or the compass to determine where modules are located In relation to the patient. For example, two modules facing each other (detected by compass) with greater than one meter distance between them may clearly indicate that the modules are on opposite sides of the patient. The more “hub”-enabled modules that reside in the operating room, the greater the achievable accuracy becomes due to triangulation techniques. The operating-room mapping module may be included in the surgical hub 20006 as described herein. The operating-room mapping module may be in operative communication with the surgical hub 20006 as described herein.

The operating-room mapping module may map the physical location of device(s) and/or surgical modules that resides within the operating room. This information could be used by the user interface to display a virtual map of the room, enabling the user to more easily identify which modules are present and enabled, as well as their current status. The mapping data collected by surgical hub 20006 may be analyzed for identifying how an operating room is physically setup, for example.

For example, the surgical hub 20006 may determine a device's location by assessing transmission radio signal strength and direction. For Bluetooth protocols, the Received Signal Strength Indication (RSSI) is a measurement of the received radio signal strength. In one aspect, the devices of the HCP monitoring system 20002 can be equipped with USB Bluetooth dongles. The surgical hub 20006 may scan the USB Bluetooth beacons to get distance information. For example, multiple high-gain antennas on a Bluetooth access point with variable attenuators can produce more accurate results than RSSI measurements. The hub surgical hub 20006 may determine the location of a device by measuring the signal strength from multiple antennas.

The surgical hub 20006 can identify components of the HCP monitoring system 20002 as they are brought into an operating room. For example, the devices of the HCP monitoring system 20002 can be equipped with an identifier recognizable by the surgical hub 20006, such as, for example, a bar code or an RFID tag. NFC can also be employed. The surgical hub 20006 can be equipped with a suitable reader or scanner for detecting the devices brought into the operating room. [Details related to Spatial awareness of surgical hubs in operating rooms, can be found in U.S. patent application Ser. No. 15/940,666, titled SPATIAL AWARENESS OF SURGICAL HUBS IN OPERATING ROOMS, filed Mar. 29, 2018, which is herein incorporated by reference in its entirety.

The computing system may be or may include an HCP monitoring system such as the HCP monitoring system 20000, 20002, 20003, or 20004 as described herein with respect to FIGS. 1-3 . The computing system may be a computing system operatively connected to the HCP monitoring system(s) 20000, 20002, 20003, and/or 20004. The computing system may be or may include the computing system 20271 described herein with respect to FIG. 9 . The computing system may be or may include the computer system 20063 described herein, for example, with respect to FIG. 4 . The computing system may be or may include the computer system 20064 described herein, for example, with respect to FIG. 4 . The computing system may be or may include the surgical hub 20006 as described herein with respect to FIGS. 1-3 , surgical hub system 20060 in FIG. 4 , the computer-implemented interactive surgical system 20070, in FIG. 5 , the surgical hub or computing device 20243 in FIG. 7 , the surgical hub 20270 in FIG. 9 , the console 20294 in FIG. 10 , and/or the surgical hub 5104 in FIG. 11 . For example, the computing system may obtain surgical monitoring data associated with one or more surgical procedures. The surgical procedures may take place in an OR or multiple ORs.

The surgical monitoring data may be obtained via the surgical hubs. For example, a surgical hub may obtain surgical monitoring data from various sensing systems such as the wearable sensing system(s) 20011, and/or environmental sensing system(s) 20015 described herein with respect to FIG. 1 . The surgical hub may obtain surgical monitoring data from HCP monitoring devices 35510, environmental monitoring devices 35512, patient monitoring devices 5124, and/or modular devices 5102 as described herein with respect to FIG. 11 . The surgical monitoring data may include situational awareness data described herein with reference to FIG. 11 .

The computing system may obtain the surgical monitoring data from various sensing systems such as the wearable sensing system(s) 20011, and/or environmental sensing system(s) 20015 described herein with respect to FIG. 1 . The surgical monitoring data may be obtained from HCP monitoring devices 35510, environmental monitoring devices 35512, patient monitoring devices 5124, and/or modular devices 5102 as described herein with respect to FIG. 11 .

The computing system may obtain surgical resource monitoring data associated with multiple surgical procedures, determine surgical resource efficiency based on the surgical resource monitoring data, and generate an output based on the determined surgical resource efficiency. The output may include but not limited to, a control signal for improving efficiency. For example, the computing system may aggregate surgical resource monitoring data associated with multiple surgical procedures and determine the surgical resource efficiency based on the aggregated surgical resource monitoring data.

FIG. 12 shows an example surgical monitoring and analysis. As shown in FIG. 12 , data inputs from multiple operating rooms such as OR1 35550, OR2 35555, through ORn 35560 may be aggregated to generate aggregated data 35570. Potential issues 35572, such as inefficient use of resources, repetitive tasks, interruptions to surgical procedure(s), task mismatch and/or deficient surgical supply stock may be identified based on the aggregated data 35570. Recommendations 35574, such as HCP task assignment adjustments, OR layout adjustments, resource allocation adjustments, and/or OR assignment adjustments may be generated based on the aggregated data 35570. Recommendations 35574 may include planning of OR(s), surgical instrument use, surgical instrument configuration, and/or capital spending to improve efficiency.

As shown in FIG. 12 , planned data may be updated based on surgical monitoring data. Using OR1 35550 as an example, planned surgical data may include, but not limited to, planned surgical procedure 35512 (e.g., procedure steps, scheduled timing and expected duration associated with the procedure steps, and/or the like), planned resource allocation 35516 (e.g., surgical instrument or other supplies associated with the procedure steps), and/or planned HCP assignment 35520 (e.g., which HCP is assigned to which surgical task(s)). Surgical monitoring data may include, but not limited to, procedure progression data 35514, actual resource utilization information 35518 (e.g., information indicating if and when a surgical instrument is used during a surgical procedure), and/or HCP monitoring data 35522 (e.g., biomarker measurements and/or biomarker indications obtained via the wearable sensing system(s) 20011 described herein, HCP movement data, HCP step monitoring data, and/or other HCP monitoring data obtained via camera(s) in the OR). Procedure progression data 35514 may indicate the type of the surgery, current step of the surgery, the HCP(s) working on the surgery and/or other information indicative of procedure progression. Procedure progression data 35514 may include the surgical procedure and the contextual information that a surgical hub may derive as described herein with respect to FIGS. 8 and 11 , and/or information that may be derived via camera-based surgical monitoring data.

As shown, planned surgical procedure data 35512 and procedure progression data 35514 may be combined to generate an updated surgical procedure plan 35532. For example, if the procedure progression data 35514 indicates a procedural step took longer than planned, the updated surgical procedure plan 35532 may be generated to reflect the delay. For example, if the procedure progression data 35514 indicates a complication has occurred, the updated surgical procedure plan 35532 may be generated with steps and/or instrument(s) to mitigate the complication.

Updated resource allocation information 35534 may be determined based on planned resource allocation 35516, actual resource utilization information 35518, and/or updated surgical procedure plan 35532. Updated HCP assignments 35536 may be generated based on planned HCP assignment 35520, HCP monitoring data 35522, HCP profile information 35524, updated surgical procedure plan 35532 and/or updated resource allocation information 35534.

Potential issues 35540, such as inefficient use of resources, repetitive tasks, interruptions to surgical procedure(s), task mismatch, the occurrence of the irregularity, accidental drop of an instrument, a potential complication, and/or deficient surgical supply stock associated with the surgical procedure taking place in OR1 may be identified, directly or indirectly, based on surgical monitoring data including procedure progression data 35514, actual resource utilization data 35518 and/or HCP monitoring data 35522. Potential issues 35540 may be identified based on the updated surgical procedure plan 35532, updated resource allocation information 35534 and/or the updated HCP assignments 35536.

Recommendations 35542 that may remediate the identified issues 35540 may be generated. For example, the computing system may generate a recommendation that additional HCP(s) outside the surgical room need to scrub and enter room. The recommendation may be generated, based on a detected surgical complication, for example. The recommendation may be sent via a display described herein, a speaker, an earpiece (e.g., ear bud, headset), a message board, etc. The recommendation may include instructions for an HCP to prepare for specific procedural steps, actions and/or other needs prior to entering the operating room.

Recommendations 35542 may be determined based, at least in part, on the surgical monitoring data. Recommendations 35542 may include HCP task assignment adjustments, OR layout adjustments, resource allocation adjustments, and/or OR assignment adjustments.

FIG. 13 shows an example surgical monitoring and aggregated analysis across multiple operating rooms. As shown in FIG. 13 , data inputs from multiple operating rooms such as OR1 35650, OR2 35655, through ORn 35660 may be considered collectively to generate updated surgical planning information for multiple operating rooms. Potential issues 35672 and recommendations 35674 for multiple operating rooms may be generated based on surgical monitoring data across the multiple operating rooms.

Surgical procedure plans for multiple ORs may be updated collectively based on surgical monitoring data across the ORs. For example, the surgical monitoring data associated with the procedure taking place in one OR may be used to update the surgical procedure plan for another procedure taking place in a different OR.

As shown in FIG. 13 , updated surgical procedure plans 35632 for OR1-ORn, updated resource allocation information 35634 for OR1-ORn, and/or updated HCP assignments 35636 for OR1-ORn may be generated based on surgical monitoring data across OR1-ORn. For example, the computing system may obtain planned surgical procedure 35512, planned resource allocation 35516, planned HCP assignment 35520, procedure progression data 35514, actual resource utilization information 35518, and/or HCP biomarker monitoring information 35522 from OR1 35650, OR2 35655 through ORn 35660 (e.g., via the surgical hub systems associated with the ORs). As described herein, the HCP biomarker monitoring information may be used to derive the HCP's fatigue level, stress level, concentration level and/or other conditions that may impact their performance during a procedure. The computing system may aggregate the obtained multi-OR surgical information and use the aggregated data to generate the updated surgical procedure plans 35632 for OR1-ORn, updated resource allocation information 35634 for OR1-ORn, and/or updated HCP assignments 35636 for OR1-ORn.

HCP profile information 35524 may include the skill set(s) of the HCPs, certifications, and/or the experience level of HCPs. For example, HCP profile information may indicate the number of years an HCP has worked on a type of task, a type of surgery, and/or in the field. HCP profile information may indicate an expected duration an HCP takes to complete a task. HCP profile information 35524 may include surgical outcomes associated with the HCPs. HCP profile information 35524 may include HCP collaboration data, such as the number of procedures certain HCPs have worked together on. HCP profile information 35524 may include hours worked (e.g., during a period of time), and/or work hours (e.g., when an upcoming shift may start, when the current shift may end).

HCP profile information 35524 may be used to predict procedure time and outcomes. The computing system may identify HCP(s) to be assigned to a procedure, or pair HCPs with surgeons to improve surgical outcome and/or efficiency.

The aggregated data 35572 may be used to determine upcoming activity levels and may identify the time and location where additional HCP(s) may be needed. The skill level and/or experiences associated with the additional HCP(s) may be determined and indicated by the computing system. The computing system may identify HCP(s) to accommodate the needs, for example, based on the HCP profile information 35524, planned HCP assignment 35520, HCP monitoring data 35522 (e.g., HCP biomarker measurements), and/or updated HCP assignment 35536. HCP skill level, experience level, availability, fatigue level and/or stress level may be determined based on the HCP profile information 35524, planned HCP assignment 35520, HCP biomarkers 35522, and/or updated HCP assignment 35536, and used by the computing system to identify HCP(s) suitable for meeting the identified needs.

The computing system may determine skillset(s) associated with a procedure, based on the type of procedure to be or is being performed, the risk of complications, the patient's characteristics, operating room layout, surgical equipment layout, surgical instrument(s) that may be used. The computing system may identify an HCP or a team of HCPs to complete the procedure based on HCP availability, the determined skillset(s) associated with the procedure, the HCPs' experience level, the HCPs' skill level, surgical outcomes associated with the HCPs and/or HCP collaboration data. The computing system may identify the best overall team to complete the procedure for the patient outcomes, efficiency and/or cost.

For example, issues 35672 may include a lack of HCP having a needed skillset in the OR during a procedure. The computing system may identify, for example, based on planned surgical procedure 35512 and/or the procedure progression 35514 information, a skillset associated with an upcoming task in the procedure. The computing system may determine whether at least one HCP in the OR possess such skillset. Upon determining a lack of HCP having this needed skillset, the computing system may send a notification to a notification device outside the OR (e.g., a device associated with an HCP scheduling personnel), indicating that the skill set is not supported within the OR. The task mismatch with the skill sets available in the OR may be identified and indicated to an HCP in the OR.

For example, the computing system may identify potential issue(s) that may inhibit the coming procedures and provide an indication of such issue(s), associated time, and/or location. For example, the computing system may identify potential issue(s) associated increased activity levels and/or special expertise and may provide an indication of such issue(s), associated time, and/or location.

As FIG. 14 show example display summarizing surgical procedures, HCP, surgical device stock status, highlighting deficiencies and recommending remediations across multiple operating rooms. The procedure summary information may indicate the type of surgery, the planned duration for each surgical step, and projected/update duration for the surgical step based on the surgical monitoring information. Procedure summary information may include planned, actual and projected HCP assignment information, planned, actual and projected surgical step information, and/or planned, actual and projected surgical resource information.

As shown in FIG. 14 , surgical planning information and surgical monitoring information across multiple ORs may be summarized and analyzed collectively. As shown, multiple surgical procedures may be carried out in different ORs, such as OR1 35750, OR2 35755, OR3 35760. Procedure summary information 35720, 35725 and 35730 for ORs 35750, 35755 and 35760 may be displayed side by side in a time aligned fashion. The procedure summary information may indicate the type of surgery associated with each OR. For example, the procedure summary information 35720 for OR1 35750 may indicate that a lung lobectomy procedure is being carried out in OR1 35750. The procedure summary information 35725 for OR2 35755 may indicate that the procedure carried out in OR2 35755 is a gastrectomy procedure. The procedure summary information 35730 for OR3 35760 may indicate that the procedure carried out in OR3 35760 is a colon laparoscopic low anterior resection procedure.

Procedure summary information 35720, 35725 and 35730 may include HCP assignment information, surgical step information, and/or surgical resource information, which may be updated in real time as the surgeries progress. HCP monitoring data 35765 may be indicated along the same timeline. As shown, the energy levels of the HCPs, for example, physician assistant a (PA-a), physician assistant b (PA-b), physician assistant c (PA-c), who are assigned to OR1 35750, OR2 35755, OR3 35760 may be indicated. Device utilization information 35770 may be indicated along the same timeline as the procedure summary information 35720, 35725 and 35730.

The procedure summary information may indicate planned surgical procedure information, surgical progression information and/or updated surgical procedure plans as described herein, for example, with respect to FIGS. 12 and 13 . As shown, time t1 may indicate the beginning of one or more procedures. Before the surgeries begin, for example, at t1 or before t1, the planned surgical procedure information, the planned resource application and/or the planned HCP assignment as described herein with respect to FIGS. 12 and 13 , may be displayed as procedure summary information. The procedure summary information may include planned surgical steps, shown in boxes, such as transect, transect IMA, stapling, mobilize meso, etc, as shown in FIG. 14 . As time progresses, the monitored procedure step start time and end time may be indicated in the procedure summary information. Present time line t4 may indicate the present time and may move as time progresses. The planned surgical steps may be updated by the computing system based on surgical monitoring data, as described herein. The monitored procedure step start time and end time (e.g., actual start and end times) may be indicated in the procedure summary information. As shown in FIG. 14 , the monitored procedure step start and completion times may be indicated via dots connected with solid lines.

The computing system may derive the actual procedural step start time and completion time based on surgical monitoring data derived via various sensing systems and/or situational awareness information as described herein. For example, the transect step in OR1 35750 may start and end later than planned. The next step may take less time than planned, and as a result the following steps may start earlier than planned. As shown, in OR3 35760, procedural step 35739 may take longer than expected, which may delay the transect step (35741 shows the planned start and end time, and 35743 shows the monitored start and end time). The computer system may determine that a complication may have occurred at 35745 during transect step. The complication may be detected based on surgical monitoring data (e.g., prolonged duration of the transect step, sudden drop of noise level in the OR, increase in measured HCP stress level and/or patient measurements). As indicated by the arrows, the timeline for the surgical procedure may be revised based on real-time surgical monitoring data. As shown, the planned start and end times for subsequent procedural steps, including transect IMA 35747, mobilize meso 35748, splenic flexure 35751 and stapling 35753, are updated (e.g., postponed, delayed) based on the detected complication 35745.

For example, the procedure summary information 35720 may indicate that a lung lobectomy is being carried out in OR1 35750. As shown, the procedure summary information 35720 may indicate that HCP PA-a is assigned to work on the lung lobectomy procedure in OR1 35750. The HCP monitoring data 35765 may include measured or derived energy level (e.g., based on biomarker measurements and/or other HCP monitoring data for an HCP) and projected energy level (e.g., energy level projected by extrapolating the measured energy level).

An HCP's energy level may be measured/determined based on biomarker measurements, for example. Based on biomarker measurements of an HCP, the computing system may determine a value associated with hydration/dehydration of the HCP. Dehydration may impact energy levels and make a person feel tired and fatigued. Less body fluid tends to increase heart rate. The computing system may analyze heartbeat data in the context of hydration levels and differentiate between stress and other heart elevation events from hydration. The computing system may employ a baseline measure to differentiate acute events from ongoing chronic events and to differentiate between fatigue and dehydration.

An HCP's fatigue level may be measured/determined based on instrument usage data, for example. The computing system may calculate a weighted measure of fatigue for the HCP operating the surgical instrument as well as others in the operating room. The weighted measure of fatigue may be based on cumulative cooperative events and contributions. For example, the weighted measure of fatigue may be based on the intensity of stress experienced by an HCP and the force exerted by the HCP over time in controlling an actuator such as closure trigger over time.

Details on energy level and fatigue level measurements are described in U.S. application Ser. No. 17/156,287 (attorney docket number END9290USNP1), titled METHOD OF ADJUSTING A SURGICAL PARAMETER BASED ON BIOMARKER MEASUREMENTS, filed Jan. 22, 2021, the disclosure of which is herein incorporated by reference in its entirety.

The HCP energy level may be compared to one or more thresholds such as good-energy threshold, moderate-risk threshold, and/or high-risk threshold. The computing system may determine HCP assignment adjustments based on the measured energy levels associated with the HCPs, the projected energy levels associated with the HCPs, the one or more HCP energy thresholds and/or the surgical procedure information (including planned and/or updated surgical procedure information). For example, upon determining that an HCP's energy level (e.g., measured and/or projected energy level) falls below a threshold, the computing system may prompt the HCP to take a break, assign the HCP a less demanding task and/or identify another HCP to assume the HCP's assigned task.

For example, as shown in FIG. 14 , the computing system, based on the measured and projected HCP energy level, may determine that PA-c is trending lower energy, with energy level dropping below the moderate-risk threshold around t3 and moving towards the high-risk threshold. The computing system may determine, for example, based on the planned procedure information and procedure progression data associated with OR3 35760, that the procedure PA-c is assigned to is a potentially long procedure. The computing system may identify another assignment for PA-c based on the surgical progression information associated with the other operating rooms. For example, a shorter and/or less risky procedure, such as procedure in OR1 35750 may be identified for HCP PA-c. The computing system may identify PA-a, whose energy level is projected to remain above the good-energy threshold, as a replacement HCP for PA-a. The timing for re-assignment may be determined based on the projected time of an HCP's energy level crossing a threshold, and/or a projected or estimated downtime for the HCP as determined based on the procedure progression information.

The computing system may notify the HCP assignment adjustment to PA-a, and PA-c. The HCP adjustment may be sent to an HCP scheduling personnel. As shown in FIG. 14 , at t2, the computing system may instruct PA-a to leave OR1 35750 and walk over to OR3 35760 to work on the procedure that takes place in OR3 35760, and instruct PA-c to leave OR1 35750 and walk over to OR3 35760 to work on the procedure that takes place in OR1 35750. At t3, the re-assignment has been completed, with PA-c working in OR1 35750, and PA-a working in OR3 35760.

Resource allocation adjustments (e.g., surgical resource change recommendations) associated with multiple ORs may be generated based on the aggregated resource allocation and utilization data. As shown in FIG. 14 , the procedure carried out in OR2 35755 may be a gastrectomy procedure, and PA-b may be assigned to work on the procedure. At t4, transection of inferior mesenteric artery (IMA) branches is performed. At 35730, the computing system may determine, for example, based on surgical monitoring data, that the planned circular stapler buttress adjunct is not acceptable for the upcoming stapling step 35735. The computing system may generate a notification requesting replacement buttress to be delivered to OR2 35755.

The computing system may identify a replacement buttress based on the planned and updated surgical procedure information associated with other ORs. For example, the computing system may determine that, based on the delay of the stapling step 35749 in OR3 35760, that the staple adjunct may not be needed and may be allocated to another OR until preparation time 35749 for stapling step 35753. For example, at 35774, the computing system may determine that the staple adjunct in OR3 35760 is not immediately used/needed and may allocate the staple adjunct to OR2 35755 until preparation time 35749.

FIG. 15 shows an example efficiency analysis based on surgical monitoring data. As shown, at 35802, surgical monitoring data associated with multiple surgical procedures may be obtained. For example, surgical monitoring data may include HCP monitoring data, surgical resource monitoring data, surgical instrument utilization data, surgical procedure progression data, instrument stock and utilization data; OR turnover data, and/or costs associated the surgical procedure(s). The computing system may obtain surgical monitoring data from one or more surgical hubs, one or more environmental monitoring device, one or more patient monitoring devices, one or more HCP monitoring devices, and/or other monitoring devices.

As shown in FIG. 15 , at 35804, surgical resource utilization adjustment(s) may be determined based on the surgical monitoring data. Surgical resource utilization adjustments may include, but not limited to, HCP task assignment adjustment(s) for reducing the distance HCP(s) need to travel to carry out the surgical procedures, OR layout adjustment(s), surgical instrument utilization allocation adjustment(s), and/or medical facility layout adjustments. At 35806, an output may be generated based on the surgical resource utilization adjustment(s). The output may include a control signal for adjusting an HCP assignment, adjusting surgery scheduling, adjusting surgical instrument allocation, adjusting surgical plan(s), notifying HCPs and/or administrators of surgical resource adjustments, notifying potential issues and/or providing recommendations. For example, the output may include a visual indication of the resource utilization adjustment(s), an audible indication of the resource utilization adjustment(s), notification(s) to HCPs inside the OR, notification(s) to HCPs outside the OR (e.g., instrumenting HCPs to be scrubbed in to provide additional support in a surgery), notification(s) to a surgical instrument supply department (e.g., requesting an instrument to be delivered to the OR), an indication to the patient's family for communicating procedure status and/or other indications. The output may include an indication of issues identified based on the surgical monitoring data, and/or recommendations for resolving or mitigating the issues.

For example, issues 35540, 35572 and/or 35672 shown in FIGS. 12 and 13 may include an irregularity, such as an error, an accident and/or an abnormality associated with a patient's anomy.

The computing system may detect an irregularity based on surgical monitoring data and generate an indication of the irregularity. For example, the computing system may predict an irregularity based on surgical monitoring data and generate an indication of the irregularity in advance of the occurrence of the irregularity. The indication may include an irregularity prevention recommendation for preemptively mitigating the irregularity.

Surgical instrument allocation for one or more procedures may be obtained and, predicted or projected surgical instrument utilization data may be determined based on the surgical instrument utilization monitoring data and the updated surgical procedure plans. For example, based on surgical monitoring data (e.g., derived based on camera-based data and/or instrument-embedded sensor-based data), the computing system may detect that a surgical instrument has been dropped. The computing system may detect that a surgical instrument has been displaced and cannot be used, for example, based on RFID zone violation. Upon the detection, the computing system may generate a notification indicating that a replacement instrument needs to be delivered to the OR. For example, the computing system may detect that the wrong-colored cartridge has been installed into a surgical stapling instrument, or that the wrong-colored cartridge is placed on the preparation table for installation into the surgical instrument. The detection of the wrong cartridge has been or is about to be installed may be made based on the surgical procedure plan 35632 and/or 35532 and procedure progression data 35514 such as video monitoring data. Upon detection, the computing system may generate a notification indicating that a replacement cartridge and/or a replacement surgical stapling device needs to be delivered to the OR. The notification for replacement instrument and/or medical supplies may be sent to a device outside of the OR, such as a notification device associated with the instrument supply room. This may enable timely instrument replacement, thus prevent, minimize, or reduce delay in the surgery caused by inadvertent errors.

For example, based on surgical monitoring data derived from imaging-based data, the computing system may detect an abnormality associated with a patient's anatomy. For example, the anatomical structures of a patient may be found in different places than would be considered normal. For example, for the majority of people, the heart can be found just slightly to the left of the sternum. However, in a condition known as dextrocardia, a person's heart may be found to the right of the sternum instead, as a mirror image of a normal cardiac anatomy. These types of abnormalities are rare, but sometimes may interfere with other systems, or have the potential to result in missed diagnoses or additional complications within surgery.

Upon detection of an abnormality associated with a patient's anatomy, the computing system may generate an adjustment to the procedure plan. The computing system may add additional surgeon(s) to the procedure, for example, to reduce the risk, or provide guidance to less experienced surgeons. The computing system may identify the surgeon(s) to be assigned and generate a notification to surgeons indicating that they should prepare to join the OR. This may reduce or minimize disruptions during a procedure. The HCPs' stress level may be reduced, knowing that an automated response system could be triggered without having to request support.

The surgical monitoring data may be compared to standard or expected surgical data to identify potential errors. For example, the computing system may determine that a procedural step has not been performed properly and/or procedural steps have been performed out of order based on surgical monitoring data. The computing system may generate a notification to request a senior HCP's support. The notification may be sent to other surgeon(s) to indicate that guidance or teaching is needed, on site in the OR or through virtual means. For example, a surgeon outside OR could access the surgical displays and coach the surgeon in the OR to perform optimized approach or steps to take.

FIG. 16 shows an example efficiency analysis based on aggregated surgical monitoring data across multiple ORs. As shown, at 35812, surgical monitoring data associated with multiple surgical procedures in operation rooms may be obtained. At 35814, surgical monitoring data across multiple ORs may be aggregated. For example, as shown in FIG. 14 , the surgical monitoring data across multiple ORs may be aggregated based on time alignment. At 35816, one or more adjustment(s), such as surgical procedure adjustments, HCP assignment adjustments, OR layout adjustments, surgical instrument utilization adjustments, and/or other adjustments as described herein may be determined based on the aggregated surgical monitoring data.

At 35818, an output may be generated based on the aggregated surgical resource utilization adjustment(s). For example, the output may include a visual indication of the resource utilization adjustment(s), an audible indication of the resource utilization adjustment(s), notification(s) to HCPs inside the OR, notification(s) to HCPs outside the OR (e.g., instrumenting HCPs to be scrubbed in to provide additional support in a surgery), notification(s) to a surgical instrument supply department (e.g., requesting an instrument to be delivered to the OR), an indication to the patient's family for communicating procedure status and/or other indications. The output may include an indication of issues identified based on the surgical monitoring data, and/or recommendations for resolving or mitigating the issues.

For example, the output may include indications may be provided to the HCP(s) to indicate ownership and responsibilities associated with the procedural steps during a procedure. The indications may be provided in real-time with audible plays to minimize interruptions and optimize efficiency.

For example, a dashboard may include indications that may identify the sequence of events (e.g., next steps), an indication of out of order step(s), and/or recommended adjustment(s). The indications on the dashboard may be generated based on planned surgical procedure data 35512, procedure progression data 35514, planned resource allocation data 35516, actual resource utilization data 35518, updated surgical procedure plan 35532 and/or updated resource allocation 35534. The recommended adjustment(s) may include, but not limited to, alter position in the OR, alter handoff of instruments, and/or cartridge replacement, for example, to optimize surgical time. As actions occur, the indications correspond to the actions on the dashboard may disappear. The dashboard may be displayed on a monitor as described herein, or a projection system that can move based on the HCPs' positions in the OR. The location of the projection may be determined such that the dashboard is projected in front of each OR personal. Surgery is stressful and can cause missed steps, or instruments, devices may not be prepared or ready when needed. The visual dashboard may utilize surgical monitoring data to track and identify when things are required from each HCP and provide details to that the HCP on the dashboard.

The computing system may monitor the HCPs' movement, as described herein. Upon detecting that an HCP leaves the OR, the computing system may determine adjustments to the ownership and responsibilities to remaining HCPs in OR and display updated indications on the dashboard. The adjustments may be indicated to the HCPs via audible indications. Other indications on the dashboard may be provided to the individual HCPs via personal audio devices. For example, indications of risks associated with a step may be provided via audio devices. The computing system may receive an indication from a lead HCP, such as a surgeon to adjust the content of the dashboard in real-time and may indicate the adjustments to other HCPs.

As described herein, HCP assignment, HCP utilization, patient throughput, medical instrument utilization, facility stock, OR turnaround and utilization may be summarized and/or aggregated.

Aggregated historic surgical procedure data may be used to recommend HCP assignment and team combinations. Historic surgical procedure data may include staffing information (e.g., HCP team combinations, HCP experience level, HCP skill set and/or the like), time, OR turnover, complication rate, patient outcomes and/or surgical resource utilization associated with surgical procedures carried out in the past.

For example, surgical outcomes (e.g., complications, success rating(s), surgery duration, or the like) may be correlated with HCP team combinations, HCP experience level, HCP skill set and/or the like. The computing system may generate HCP assignment recommendations, such as recommending specific HCP for a specific procedure, recommending a specific HCP for a specific task, and/or recommending a team combination for a procedure, based on the surgical outcome-HCP correlation data.

FIG. 17 shows an example updating of surgical procedural plans based on surgical monitoring data. As shown, at 35822, surgical monitoring data associated with multiple surgical procedures in operation rooms may be obtained. At 35824, surgical monitoring data across multiple ORs may be aggregated. At 35826, surgical procedure plans may be updated based on the aggregated surgical monitoring data.

Based on the aggregated data, the computing system may generate surgical planning information. For example, the computing system may, based on the aggregated historic surgical procedure data, determine surgical device allocation for a particular surgeon. For example, the surgical device most frequently used by the surgeon for the procedural step may be selected for inclusion in the surgical planning information. The computing device may, based on the aggregated historic surgical procedure data, determine surgical device allocation for a patient having one or more characteristics. The computing device may, based on the aggregated historic surgical procedure data, determine surgical device allocation for a particular procedure. For example, the surgical device most frequently used for the procedure in past surgeries may be selected for inclusion in the surgical planning information. For example, the surgical device associated with the highest recovery rate in past surgeries may be selected for inclusion in the surgical planning information.

Based on the aggregated data, the computing system may generate daily OR planning recommendations. Daily OR planning recommendations may include recommended OR(s) for upcoming surgeries, recommended surgery time, recommended HCP work hours and breaks. The computing system may predict staff shortages or overages based on the aggregated data. The aggregated data may be used to optimize HCP work.

The computing system may, based on the aggregated surgical procedure monitoring data, generate procedure plan(s) based on staff availability, instrument availability, and specialized OR equipment. For example, the computing system may determine that a specialized OR equipment may be needed for a procedure. The computing system may identify a time during which the instrument and at least one HCP having experience/skill set associated with the instrument are available and generate a procedure plan based on the identified time.

FIG. 18 shows an example adjustments of HCP assignments based on aggregated surgical monitoring data across multiple ORs. As shown, at 35832, surgical monitoring data associated with multiple surgical procedures in operation rooms may be obtained. At 35834, surgical monitoring data across multiple ORs may be aggregated. At 35836, HCP assignments may be updated based on the aggregated surgical monitoring data.

The computing system may generate surgical planning recommendations based on surgical monitoring data associated with multiple surgical procedures. Large scale facility variables may be incorporated into surgical planning recommendation generation. Such variables may include, but not limited to, HCP availability, HCP stress level, HCP fatigue level, various HCP biomarkers, OR capacity, budget, patient volume, surgical outcomes, time of day, weather, and/or surgical device or surgical equipment availability, across multiple operating rooms. For example, availability for the HCPs in the surgical department of a hospital having multiple operating rooms may be considered when the computing system generates surgical planning recommendations.

A 2006 study found that the 146 nurses studied walked an average of 4-5 miles during a 12-hour shift, while most Americans walk just 2.5-3 miles during the course of an 18-hour day. The kind of walking nurses do at work has very little cardiac or stress-relieving benefits. In fact, walking that far during a shift can lead to fatigue, which could potentially reduce the quality of patient care.

The computing system may calculate an indication of a total distance traveled by an HCP who simultaneously work on multiple surgical procedures based on the HCP monitoring data. The computing system may obtain step monitoring data, such as distance traveled (e.g., during a period of time) for an HCP via one or more HCP wearable sensing systems and/or environmental sensing system(s) described herein. The computing system may determine suggested break time, fluid intake, food intake, and/or shoe replacement time for an HCP based on step monitoring data associated with the HCP. The computing system may provide an indication to prompt the HCP to take a break, suggest fluid and/or food intake, and/or prompt the HCP when shoes should be replaced, for example, when the distance traveled by the HCP during a time period exceeding a threshold.

The frequency of activities that require nurses to walk may impact the total distance traveled on a given shift. Operational factors that affect the total frequency may include the nurse-to-patient ratio, staffing, the type of patient population, and/or whether it is a day, evening or night shift.

The computing system may determine staff shortage and/or overage based on HCP step monitoring data. For example, staff monitoring data may include an indication of the distance traveled by different HCPs during different shifts. Upon determining that the average distance traveled per HCP during a shift exceeds a threshold, the computing system may recommend adding additional HCP(s) to the shift. Upon determining that the average distance traveled per HCP during a shift is less than a threshold, the computing system may recommend reducing HCPs during the shift. Based on comparing that the average distance traveled per HCP during a first shift and the average distance traveled per HCP during a second shift, the computing system may identify HCP(s) being transferred between the two shifts.

The computing system may identify changes to the workflow of an HCP based on HCP step monitoring data. For example, the HCP step monitoring data for an HCP may include the amount of steps traveled and the path traveled by the HCP, for example, obtained via one or more HCP wearable sensing system(s) and/or environment sensing system(s) described herein. The computing system may identify repetitive trips based on the path traveled by the HCP. The computing system may identify one or more tasks associated with the repetitive trips. For example, surgical procedure progression data associated a surgical procedure may be obtained. A set of repetitive trips made by an HCP may be identified based on the HCP step monitoring data. One or more task(s) associated with the repetitive trips made by the HCP may be identified by correlating the surgical procedure progression data with the repetitive trips made by the HCP. The computing system may determine a task assignment adjustment for reducing the distance traveled associated with the identified surgical task(s). For example, the computing system may determine a simplification of the identified task(s) that may reduce travel. The computing system may determine a time or scheduling change associated with the identified task(s). For example, the computing system may recommend one or more identified task be carried out in down time. Certain tasks that are planned to be performed during a procedure may be identified to be performed during pre-operative preparation.

The computing system may determine patient admission times based on surgical planning data and/or surgical monitoring data for reducing the distance traveled by the HCP(s). The patient admission times may be determined such that the HCP(s) may perform the same or similar tasks associated with multiple patients during the same trip.

The computing system may identify a set of combinable tasks based at least on the surgical procedure progression data and may recommend combining the identified set of combinable tasks. The combinable tasks my include the same or similar tasks associated with multiple patients. The combinable tasks my include the same or similar tasks associated with multiple operating rooms. The computing system may, based on the surgical monitoring data and/or surgical planning data, handle patient guidance and intake planning and notifications. The computing system may notify the HCP when and where to pick up the patient(s) to accomplish the steps that require interaction, allowing the HCP to support multiple patients at the same time and limiting their repetitive tasks. The workflow change recommendations may be provided to a notification device of the HCP, and/or a notification device associated with a facility scheduling personnel.

The computing system may determine that patient pickups may be combinable and may notify the HCP to pick up multiple patients during a single trip. For example, the computing system may identify, based on the surgical procedure progression data and/or the surgical planning data across multiple ORs, that multiple patients may start surgery around the same time. The computing system may generate notification(s) to the HCP(s), advising of the pickup time(s), locations and that the patients are to be picked up during the same trip. The computing system may generate notification(s) to the identified patients (e.g., to devices associated with the identified patients), advising the patients of the pickup time(s). For example, the computing system may identify, based on the surgical procedure progression data and/or the surgical planning data across multiple ORs, that surgical instruments and/or medical supplies are needed for multiple ORs. The computing system may notify an HCP to pick up and deliver the surgical instruments and/or medical supplies to the multiple ORs during the same trip.

The computing system may identify changes to the layout within the healthcare facility based on HCP step monitoring data. As described herein, the computing system may identify one or more tasks associated with the repetitive trips made by an HCP. The computing system may identify an aspect of OR layout associated with the identified surgical task(s) and generate an OR layout adjustment for reducing a path length associated with the set of repetitive trips. The computing system may identify an aspect of the healthcare facility layout associated with the identified repetitive task(s) and generate a healthcare facility layout adjustment for reducing a path length associated with the set of repetitive trips.

A computing system may determine a virtual boundary associated with a restricted access in an OR. The virtual boundary described herein may be or may include an area associated with a restricted access in the OR. For example, the area associated with a restricted access in the OR may be an enclosed area, such as a circle, an oval, a rectangle, a square, and/or the like.

FIG. 19 illustrates examples of one or more virtual boundaries associated with restricted accesses in an OR. As illustrated in FIG. 19 , an OR 36000 may include one or more virtual boundaries, and each of the virtual boundaries may be associated with corresponding restricted accesses.

A virtual boundary may be associated with a restricted access area for an anesthesiologist in an OR. The restricted access area may be referred to as virtual boundary area herein. For example, a virtual boundary area for an anesthesiologist 36005 may be or may include a restricted access area for an anesthesiologist, e.g., as illustrated in FIG. 19 . The virtual boundary area for an anesthesiologist 36005 may limit access to health care professionals (HCPs) in an OR and may allow access to an anesthesiologist, an anesthesiologist staff, and/or an anesthesiologist equipment. For example, an anesthesiologist may be allowed to enter, exit, and/or be stationed in the virtual boundary area for an anesthesiologist 36005, e.g., during a surgical procedure. As described herein, a computing system may determine a virtual boundary associated with a restricted access area for an anesthesiologist 36005. The computing system may monitor movement of HCPs in an OR. If the computing system determines that an HCP, other than an anesthesiologist and/or an anesthesiologist staff, is in a proximity to the virtual boundary area for an anesthesiologist 36005 and/or attempts to enter or interact with the virtual boundary area for an anesthesiologist 36005, the computing system may send a notification to the one or more HCPs. The notification may indicate that the HCP does not have an access authorization to enter or interact with the virtual boundary area for an anesthesiologist 36005.

A virtual boundary area for an anesthesiologist 36005 may be or may include one or more subsets of virtual boundary areas relating to an anesthesiologist. For example, a virtual boundary area 36010 may be associated with an area where an anesthesiologist is stationed during a surgical procedure. A virtual boundary area 36015 may be a virtual boundary area for an anesthesiologist staff, such as an anesthesiologist nurse, and/or an anesthesiologist equipment, such as a display for an anesthesiologist. A virtual boundary area 36020 may be a virtual boundary area where an anesthesiologist instrument for an anesthesiologist may be stationed.

A virtual boundary area may be associated with a restricted access area for a surgeon in an OR. For example, a virtual boundary area associated with a restricted access area for a surgeon 36025 may be illustrated in FIG. 19 . The virtual boundary for a surgeon 36025 may be a restricted access area for a surgeon in an OR to enter, exit, and/or be within during a surgical operation. The virtual boundary for a surgeon 36025 may be or may include a restricted access area where a surgeon operates during a surgical step of an operation. The virtual boundary area for a surgeon 36025 may limit access to a surgeon who is/will be operating in a current surgical step. For example, a computing system may determine a virtual boundary area for a surgeon 36025 in an OR 36000. The computing system may monitor movements for HCPs in the OR. For a current surgical step, the computing system may identify a surgeon, such as a lead surgeon, who is going to preform the current surgical step. The computing system may allow the lead surgeon to access the virtual boundary area for a surgeon 36025 (e.g., to enter, exit, or be stationed). If the computing system determines that an HCP other than the identified surgeon is in a proximity to the virtual boundary area for a surgeon 36025 or about to enter/interact with the virtual boundary area, the computing system may send a notification to the HCP alerting that the HCP does not have an access authorization to enter or interact with the virtual boundary area for a surgeon 36025 and limit the access.

As described herein, the virtual boundary area for a surgeon 36025 may be or may include one or more subset of restricted access area (not illustrated). For example, a subset of the virtual boundary area for a surgeon 36025 may include a virtual boundary area for a surgeon who is performing a current surgical step of an operation. A subset of the virtual boundary area for a surgeon 36025 may include a virtual area for an assistant surgeon for a surgical procedure. A subset of the virtual boundary area for a surgeon 36025 may include a virtual boundary area for an observer, such as an intern. The computing system may allow the identified HCP, such as a surgeon, an assistant surgeon, and/or an observer, to access the corresponding virtual boundary area and limit the access to other HCPs.

A virtual boundary may be associated with a restricted access area for a surgical table in an OR. For example, a virtual boundary associated with a restricted access area for a surgical table 36030 may be illustrated in FIG. 19 . The virtual boundary area for a surgical table 36030 may be a restricted access area that allows a surgeon, such as the surgeon who will be performing a current step of a surgical procedure and/or a patient. For example, the virtual boundary area for a surgical table 36030 may be a sterilized area where a patient is positioned for a surgical operation. The virtual boundary area for the surgical table 36030 may be sterilized. The computing system may limit access to the virtual boundary area for a surgical table 36030. For example, the computing system may allow a patient to enter and be positioned in the virtual boundary area for a surgical table 36030. The computing system may control an access to the virtual boundary area for a surgical table 36030 and allow an HCP who has an access authorization to the virtual boundary area for a surgical table 36030 to enter, exit, and/or be stationed. As described herein, the computing system may send a notification to an unauthorized HCP to enter or interact with the virtual boundary area for a surgical table 36030 and block the access.

A virtual boundary may be associated with a restricted access area for a scrub nurse. For example, a virtual boundary associated with a restricted access area for a scrub nurse 36035 may be illustrated in FIG. 19 . As described herein, the virtual boundary area for a scrub nurse 36035 may be a restricted access area that allows a scrub nurse to enter, exit, and/or be stationed, e.g., during a surgical procedure. The computing system may allow a scrub nurse, who has an access authorization, to interact with or be in the virtual boundary area for a scrub nurse 36035. The computing system may block an unauthorized HCP to access or interact with the virtual boundary area for a scrub nurse 36035 and send a notification to the unauthorized HCPs.

A virtual boundary may be associated with a restricted access area for a circulating nurse. For example, a virtual boundary associated with a restricted access area for a circulating nurse 36040 may be illustrated in FIG. 19 . As described herein, the virtual boundary area for a circulating nurse 36040J may be a restricted access area that allows a circulating nurse to enter, exit, and/or stationed, e.g., during a surgical procedure. The computing system may allow a circulating nurse who has an access authorization to interact with or be in the virtual boundary area for a circulating nurse 36040. The computing system may send a notification to an unauthorized HCP and may block the access of the unauthorized HCP accessing or interacting with the virtual boundary area for a circulating nurse 36040.

A virtual boundary area may be associated with one or more restricted access areas for a surgical instrument, sterile tray table, and/or other surgery related equipment. For example, a virtual boundary associated with a restricted access area for a surgical instrument, a sterile tray table, and/or other surgery related equipment 36045, 36050, 36055, 36060, 36065 may be illustrated in FIG. 19 . Examples of surgery related equipment may include one or more of: a filtration system, a particle capture system, and/or an airborne contamination zone. As described herein, the computing system may allow an HCP with an access authorization to allow entering, exiting, interacting with, and/or be stationed in the virtual boundary area for the surgical equipment. For example, a scrub nurse who has an access authorization to enter a virtual boundary area for a sterile tray table 36045 may enter/exit the virtual boundary area for a sterile tray table 36045 during a surgical operation. The computing system may block other HCPs who do not have the access authorization to interact with (e.g., enter) the virtual boundary area for a sterile tray table 36045 from interacting with the virtual boundary area for a sterile tray table 36045. The computing system may send a notification to the unauthorized HCPs indicating that the HCPs do not have access authorizations to enter the virtual boundary area for a sterile tray table 36045.

As illustrated in FIG. 19 , one or more virtual boundary areas may overlap. For example, a virtual boundary area for a surgeon 36025 may be inside of a virtual boundary area for a surgical table 36030. In examples, during a surgical operation, a scrub nurse may be assisting a surgeon by hand over a surgical instrument to the surgeon. A virtual boundary area for a scrub nurse 36035 may overlap with a virtual boundary area for a surgeon 36025 and/or a virtual boundary area for a surgical table 36030.

A virtual boundary associated with a surgical instrument and/or a virtual boundary associated with a patient may change. For example, a virtual boundary associated with a restricted access area for a surgical instrument may change based on the surgical instrument being in an off position or being in an on position (e.g., while the surgical instrument is in use during a surgical procedure). A virtual boundary area associated with a patient may change during a surgical procedure as the body of the patient is moved, turned, repositioned, or etc.

FIG. 20 illustrates other examples of one or more virtual boundaries associated with restricted accesses in an OR 36100. As described herein, a virtual boundary may be associated with a restricted access area for an anesthesiologist 36105. A virtual boundary area for an anesthesiologist 36105 may include a virtual boundary area for an anesthesiologist nurse 36110. As an anesthesiologist nurse assists an anesthesiologist during a surgical procedure by handing over an anesthesiologist equipment, the anesthesiologist nurse may have access to enter, exit, and/or be stationed inside of the virtual boundary area for an anesthesiologist 36105.

As described herein, a virtual boundary may be associated with a restricted access area for a surgical table and/or an operation area 36120. A virtual boundary area for a surgical table and/or an operation area 36120 may include a virtual boundary area for a surgeon 36115. As a surgeon needs to operate a patient who is on a surgical table, the surgeon may be authorized to interact with (e.g., enter, exit, be stationed inside of) the virtual boundary area for a surgical table and/or an operation area 36120.

As described herein, a virtual boundary may be associated with a restricted access area for a nurse 36125. A nurse may assist a surgeon during a surgical procedure. For example, a nurse may hand a surgical instrument to a surgeon. The nurse may be authorized to interact with or enter, exit, and/or be stationed in the virtual boundary area for a surgeon 36115 and/or the virtual boundary area for a surgical table and/or an operation area 36120.

A virtual boundary may be associated with a restricted access area for an assistant 36130. An assistant may answer a device associated with one or more HCPs in an OR. For example, an assistant may answer a cellphone and/or a pager for a surgeon. As a role for an assistant may be non-surgical related, an access authorization associated with an assistant may be at a minimum level (e.g., a default level or a basic level). For example, an assistant may not have an access authorization to interact with, enter, exit, be stationed in other virtual boundaries in an OR. In addition to and/or alternatively, a virtual boundary area for an assistant 36130 may be used as a boundary or a barrier for a computing device to monitor movement of an assistant. For example, in case an assistant exits and/or leaves a virtual boundary area for an assistant 36130, the computing system may send a notification to the assistant. The notification may indicate that the assistant may be outside of the virtual boundary area designated for an assistant 36130 and may potentially contaminate other virtual boundary areas with sterilized fields.

As described herein, a virtual boundary may be associated with a restricted access area for an observer 36135. An observer may be stationed close to (e.g., next to or in proximity to) a surgical table to observe a surgical procedure. An access authorization associated with an observer may be at a minimum level (e.g., a default level or a basic level). For example, a role for an observer is to observe a surgical procedure and not to interfere with the surgical procedure. An observer may not have an access authorization to interact with, enter, exit, be stationed in other virtual boundaries in an OR. In addition to and/or alternatively, a virtual boundary for an observer 36135 may be used as a boundary or a barrier for a computing device to monitor movement of an observer. For example, if an observer exists and/or leaves the virtual boundary area for an observer 36135, the computing system may send a notification to the observer. The notification may indicate that the observer may be outside of the virtual boundary area designated for an observer 36135 and may contaminate other virtual boundary areas with sterilized fields.

As illustrated in FIG. 20 , a virtual boundary may be associated with a restricted access area for a surgical safety checklist (SSC) 36140. In examples, a computing system may determine whether an HCP is wearing personal protection equipment (PPE). If the computing system determines that the HCP is not wearing proper PPE for a surgical operation, the computing system may send a notification to the HCP. The notification may indicate that the HCP is in proximity to the virtual boundary area for an SSC 36140 and the HCP and may not be wearing PPE. In examples, the computing system may allow an HCP to enter the virtual boundary area for an SSC 36140. The computing system may determine whether the HCP is wearing PPE suitable for a surgical procedure (e.g., when the HCP is in the virtual boundary area for an SSC 36140). If the computing system determines that the HCP is n proximity to the virtual boundary area for an SSC 36140 and is about to exit and/or leave the virtual boundary area for an SSC 36140, the computing system may send a notification to the HCP. The notification may indicate to the HCP that the HCP is not wearing proper PPE suitable for the surgical procedure and may be exposed to danger if the HCP exits and/or leaves the virtual boundary area for an SSC 36140.

A virtual boundary associated with a restricted access area described herein may be associated with a virtual boundary area (e.g., a constant virtual boundary area), a selective boundary area, and/or an adaptive boundary area. FIG. 21 illustrates examples of a virtual boundary area (e.g., a constant virtual boundary area), a selective virtual boundary area, and/or an adaptive virtual boundary area in an OR 36200. A virtual boundary area (e.g., a constant virtual boundary area) may be associated with a predefined and/or a preconfigured equipment area in an OR. For example, a virtual boundary area may be associated with a sterile field area for operating zone 36205, a virtual boundary area for anesthesiologist 36210, a virtual boundary area for a surgical instrument, such as a high energy equipment area 36215 and/or the like. The virtual boundary area described herein may be unchanged (e.g., unadjusted or constant). A virtual boundary area may be associated with a high-risk area. For example, a high-risk area may be associated with an operating zone for an infectious disease, contagious disease, and/or a surgical operation with a radioactive material.

A virtual boundary area may be a predefined area around an equipment area in an OR, e.g., based on a preference of a surgeon, a guideline of a hospital, a health organization protocol, and/or the like. A virtual boundary area may be a predefined area around a high-risk area (e.g., following a guideline of a health agency, such as the Centers for Disease Control and Prevention, the World Health Organization, and/or the like).

A virtual boundary area associated with an equipment area may be adjusted. An equipment area and/or a high-risk area may be moved and/or shifted, e.g., during a surgical procedure. Based on the moved and/or shifted area of an equipment area and/or a high-risk area, a virtual boundary area for the equipment may be moved and/or shifted accordingly (e.g., with the equipment).

A virtual boundary area for an equipment area and/or a high-risk area may be adjusted, e.g., self-adjusted automatically. In examples, a surgical equipment may be moved and/or shifted when the surgical equipment is in an on position or in an off position (e.g., as will be illustrated and described in FIG. 22 ). The virtual boundary area associated with the surgical equipment may be self-adjusted accordingly. In examples, during a surgical operation, the body of a patient may be repositioned and/or moved. Based on the repositioned and/or moved body of the patient, the virtual boundary area associated with a high-risk area may be adjusted accordingly.

A virtual boundary area for an equipment area and/or a high-risk area may be adjusted by the computing system. In examples, the computing system may determine whether a surgical equipment is in an on position or in an off position. The computing system may adjust a virtual boundary area for an equipment area when the computing system determines that a surgical equipment is in an on position or in an off position.

In examples, the computing system may monitor and/or track the body position of a patient during a surgical operation. The computing system may determine that a patient is a high-risk area. If the computing system determines that the body position of the patient has been repositioned, moved, adjusted, and/or the like, the computing system may adjust the virtual boundary area for a high-risk area (e.g., associated with the body of the patient).

A virtual boundary area for an equipment area and/or a high-risk area may be adjusted by an HCP. In examples, a surgical instrument may be moved by an HCP during a surgical procedure. The HCP may adjust the virtual boundary area for the surgical instrument as the surgical instrument is being moved. In examples, an HCP may reposition the body of a patient for a current surgical step or procedure. Based on the reposition of the patient, the HCP may adjust the virtual boundary area associated with a high-risk area (e.g., associated with the body of the patient) accordingly.

A virtual boundary associated with a restricted access area described herein may have a selective boundary area. For example, an HCP, such as a surgeon, may define a virtual boundary area of an operating zone around a patient. As illustrated in FIG. 21 , such area may be focused on or around a stomach of a patient 36220. A surgical instrument, such as a high energy surgical instrument, may be activated inside of a selective virtual boundary area, e.g., on or around the stomach of the patient 36220. The surgical instrument may be inactive outside of the selective virtual boundary area. For example, the computing system may identify a selective virtual boundary, e.g., generated by an HCP. The computing system may monitor a location and/or a position of a surgical instrument. The computing system may monitor an energy state of the surgical instrument. If the computing system determines that the surgical instrument is located and/or positioned within the boundary of the selective virtual boundary area, the computing system may generate a signal to activate the surgical instrument (e.g., transition from a low energy state to a high energy state). If the computing system determines that the surgical instrument is located and/or positioned outside the selective virtual boundary area and/or if the energy state of the surgical state has been activated while outside of the selective virtual boundary area, the computing system may generate a signal to deactivate the surgical instrument. The computing system may send an alert to an HCP indicating that the surgical instrument has been activated outside of the selective virtual boundary area.

A virtual boundary associated with a restricted access area described herein may have an adaptive boundary. During a surgical procedure, the body of a patient may be repositioned or moved. A selective virtual boundary of a surgical instrument (e.g., generated by an HCP) may be changed or adjusted upon detecting the reposition and/or movement. For example, as illustrated in FIG. 21 , the body of a patient may be repositioned (e.g., repositioned to its side) and the selective virtual boundary area may be reduced and/or an arm of the patient may be in the selective virtual boundary area where a surgical instrument may be allowed to be in a high energy state. An adaptive virtual boundary area 36225 may be generated based on the change and/or reposition of the body of the patient, and the surgical instrument may not be activated in a high energy state to the repositioned arm area of the patient.

The computing system may generate an adaptive virtual boundary area and/or identify an adaptive virtual boundary area generated by an HCP. For example, the computing system may monitor a position of a patient and a selective virtual boundary area. If the computing system detects and/or determines that the position the patient has been changed and/or the selective virtual boundary area needs to be adjusted, the computing system may generate an adaptive virtual boundary area to accommodate for the change. The adaptive virtual boundary area may be temporary and may be turned off if the body of the patient is changed (e.g., changed back to the earlier position). An HCP may generate an adaptive virtual boundary area. As an HCP repositions the body of a patient, the HCP may indicate an adaptive virtual boundary area to the computing system, and the computing system may identify the adaptive virtual boundary area defined by the HCP.

A virtual boundary described herein may be preconfigured by an HCP. For example, an HCP preparing for a surgical procedure may preconfigure one or more virtual boundary areas in an OR. The virtual boundary areas may be based on a placement of surgical instruments, a placement of a surgical table, a placement of a surgical sterile tray table, an anesthetist zone, and/or the like. An HCP may manually input and/or adjust the virtual boundary areas.

The computing system may determine one or more virtual boundary areas based on past data associated with HCPs and/or a surgical procedure. For example, the computing system may determine that the same surgical procedure has been performed by the same HCPs. Based on the past data, the computing system may preconfigure the one or more virtual boundary areas. The past data may be or may include data from a different OR, preferences of HCPs, pre-op data, and/or the like.

As described herein, a surgical operation may be associated with an infectious disease, airborne contamination, and/or the like. A virtual boundary may be created for an infectious disease control tracking, airborne contaminate zone monitoring, and/or the like. For example, a virtual boundary may be associated with a filtration system area, a particle capture system area, an airborne contamination zone, and/or the like.

The computing system may identify an HCP in an OR. As described herein, the computing system may identify an HCP based on ID tag, camera feed, facial recognition, and/or the like. Based on the identification of the HCP in an OR, the computing system may determine an access authorization associated with the HCP. The computing system may look up, download, and/or determine the access authorization associated with the HCP. The access authorization may be or may include access authorization information for respective HCP to interact with, enter, exit, and/or be positioned within a virtual boundary area.

The computing system may monitor a movement of the identified HCP in the OR. For example, the computing system may track the movement of the HCP. The computing system may monitor the movement of the HCP, e.g., based on a camera system in the OR, RFID tag associated with the HCP, and/or the like.

Based on the monitored movement of the HCP and the access authorization associated with the HCP, the computing system may determine whether the HCP has an access authorization to interact with a virtual boundary associated with a restricted access area. As described herein, a virtual boundary associated with a restricted access area may be associated with a surgical equipment area, a high-risk area, an infectious disease control area, an air borne contamination area, and/or the like.

If the computing system determines that an HCP does not have an access authorization to interact with or enter (e.g., unauthorized to enter) a virtual boundary associated with a restricted access area and is in a proximity to the virtual boundary area, the computing system may send a notification to the HCP. The notification to the HCP may indicate that the HCP is unauthorized to interact with or enter the virtual boundary area. The computing system may send the notification to a device associated with the HCP, and the notification may be or may include one or more of a visual notification, an audio notification, a haptic notification, or an augmented reality notification. The computing system may send a notification to a display in the OR and/or a device associated with one or more other HCPs in the OR.

After sending a notification to the HCP who is unauthorized to interact with or enter the virtual boundary area, if the computing system determines that the HCP continues to approach the virtual boundary area and/or move closer to the virtual boundary area, the computing system may send a notification to a display in the OR and/or a device associated with one or more other HCPs in the OR and may alert one or more other HCPs in the OR.

If the computing system determines that an HCP has an access authorization to enter a virtual boundary associated with a restricted access area, the computing system may allow the HCP to interact with, enter, exit, and/or be positioned within the virtual boundary area. For example, the computing system may skip sending a notification to the HCP.

As described herein, a virtual boundary may be associated with a static (e.g., constant) boundary around a sterile field area. The computing system may monitor movements of HCPs in an OR and may send a notification to one or more HCPs who are not wearing proper sterile equipment. For example, the computing system may send a notification to an HCP who is not wearing sterile gown and/or is uncertified for entering a virtual boundary of a sterile field area as the HCP is approaching a proximity area of the virtual boundary area for the sterile field. After sending the notification to the HCP and if the computing system determines that the HCP is about to interact with (e.g., enter) the virtual boundary area for a sterile field area, the computing system may send a notification to a display in the OR and/or other HCPs, such as a scrub nurse and/or to broadcast the notification to the OR at large, to block or intervene the unauthorized HCP from interacting with or entering the virtual boundary area for a sterile field area. The computing system may prevent potential contamination in the virtual boundary area for a sterile field area by sending the notification and blocking the unauthorized HCP from interacting with the virtual boundary area.

As described herein, a virtual boundary may be associated with an area for treating an infectious patient. A dynamic constant virtual boundary may be created around the area where aerosolized particles can be loose. The virtual boundary for the area may be associated with a filtration system area and/or a particle capture system area. The computing system may monitor a movement of an HCP in an OR. The computing system may identify HCPs with PPE in the OR and/or HCPs with certificates or access authorizations to handle a contagious and/or infectious surgical operation, such as treating an infectious patient. If the computing system determines that an HCP does not have a PPE, a certificate, and/or an access authorization to enter the virtual boundary area for an infectious patient, the computing system may send a notification to the HCP. The computing system may alert the HCP, using the notification, to stay away the virtual boundary area for the infectious patient, e.g., via the notification.

A virtual boundary associated with a restricted access area may be or may include an equipment area. As described herein, a virtual boundary for an equipment area may be a predefined boundary surrounding the equipment area. As the equipment moves around during a surgical procedure, the virtual boundary around the equipment may stay constant. For example, a constant predefined virtual boundary area may be generated for a monitor, a surgical table, a sterile table, a surgical equipment, and/or the like. The constant predefined virtual boundary may exist during the surgical procedure. The computing system may monitor (e.g., keep track of) a movement of the equipment during the surgical procedure. The computing system may keep unauthorized HCP(s) out of the virtual boundary area for the equipment as the equipment gets moved around during the surgery. The computing system may allow an authorized HCP to interact with, enter, exit, be located within the constant predefined virtual boundary area for the equipment.

A surgical instrument, such as a robotic arm illustrated in FIG. 22 , may send a notification to one or more HCPs in the OR. For example, prior and/or during a movement, a surgical instrument may indicate to the HCPs in the OR that a movement is occurring. The surgical instrument and/or the computing system may indicate a virtual boundary area where the movement will end and display the adjusted area to HCPs. For example, the computing system may provide a visual indication (e.g., such as a colored laser) to indicate the adjusted location of the virtual boundary area associated with the surgical instrument. The visual indication may allow the unauthorized HCPs to keep out of the virtual boundary area for the surgical instrument and allow the authorized HCPs to relocate to be in the virtual boundary, if necessary.

An HCP and/or an equipment may block a movement, e.g., an end movement, of a surgical instrument. If the surgical instrument determines that the surgical instrument cannot reach a full end movement, the surgical instrument may send a notification to an HCP. For example, the surgical instrument may provide an audible alert to the HCP to move out of the way, ask the HCP to move the equipment that is blocking the surgical instrument reaching the end movement, and/or ask the HCP to readjust the surgical instrument. The surgical instrument may provide a visual indication to the HCP, e.g., to ensure that the surgical instrument does not make contact with an HCP and/or an equipment, does not disrupt a current surgical procedure, and/or cause an injury.

As described herein, a virtual boundary may be associated with a selective virtual boundary area. For example, a selective virtual boundary area may be based on a usage of an equipment in an OR. A selective virtual boundary area may be adjusted based on an energized state of a surgical instrument. For example, if the computing system determines that a surgical instrument is in an off mode and/or in a low energized state, the computing system may determine or identify a selective virtual boundary area to allow access to one or more HCPs, such as a surgeon, a scrub nurse, an observer, or etc. If the computing system determines that a surgical instrument is in a high energized state (e.g., a surgeon using the surgical instrument during a current surgical step), the computing system may adjust the selective virtual boundary area to exclude other HCPs who are not using the surgical instrument. For example, if the surgical instrument is in a high energized state, the computing system may block other HCPs and allow access to the surgeon who is performing a current surgical step.

A selective virtual boundary area associated with a surgical instrument may be set based on which arms are active and/or where the arms of the surgical instrument are positioned and can reach. For example, if the surgical instrument (e.g., the arms of the surgical instrument) is in an off mode and/or not moving, the selective virtual boundary area may be removed (e.g., temporarily and/or until the arms are operating).

FIG. 22 illustrates an example surgical instrument with an arm in an OR 36300. The surgical instrument may be in an off mode and a virtual boundary area associated with the off mode 36305 may be generated. A virtual boundary area of the arm of the surgical instrument may be in an off position 36315. If the surgical instrument is operating and/or is in an on mode, a selective virtual boundary area around the surgical instrument associated with an on mode 36310 may be generated. The selective virtual boundary area around the surgical instrument for the on mode 36310 may have a larger area than the virtual boundary area associated with the off mode 36305 and allow the surgical instrument to move around. A selective virtual boundary area of the arm of the surgical boundary associated with an on position 36320 may be generated. The selective virtual boundary 36320 may be adjusted based on a space that the arm can occupy while in use (e.g., while operating). For example, the selective virtual boundary area of the arm of the surgical instrument in the on mode 36320 may cover a sweeping motion of the arm moving.

For example, the surgical instrument shown in FIG. 22 may be an imaging system. For example, a hybrid OR may be built around an imaging device. For example, an imaging device may be a non-mobile imaging device, such as a computerized x-ray imaging (CT) device, magnetic resonance (MR) device, and/or the like. The imaging device may include a high energy imaging component that needs to be avoided by an HCP, e.g., via a virtual boundary area. The imaging device may include a boom and/or other movable component that may need repositioning manually or under power. The boom of the image device may have a selective virtual boundary area when the image device is being used. When the boom is being used, the selective virtual boundary area may be generated to prevent an HCP from an inadvertent interaction with the imaging device and/or any hazards associated with the imaging device.

The imaging device may be a mobile imaging system, e.g., as illustrated in FIG. 22 . The mobile imaging system may be moved into and/or within an OR. The mobile imaging system may be manipulated to the site where an imaging is needed, e.g., via a stable arm. The envelope of positioning and/or the exposure area of the mobile imaging system may have corresponding selective virtual boundary areas.

Example mobile imaging system may be fluoroscopy, such as a C-Arm X-ray, a 3D imaging machine, and/or an ultrasonic imaging. As illustrated in FIG. 22 , a stable arm of a mobile imaging device may have a selective virtual boundary area when the image device is being used. The selective virtual boundary for the stable arm of the mobile imaging device 36325 may be focused on or around an arm of a patient that needs an imaging review. When the stable arm of the imaging device is operating, the selective virtual boundary area 36325 may be generated to prevent HCPs from inadvertent interactions with the imaging device and/or any hazards associated with the imaging device.

A virtual selective boundary associated with an imaging device described herein may be outlined to a floor of an OR. The virtual selective boundary associated with an imaging device may include vertical boundaries, or three-dimensional boundaries. For example, a mobile system, illustrated in FIG. 22 , may need a pace, e.g., a 2 ft spherical boundary, 3 ft off the floor, and may be focused on an imaging site of an arm of a patient for review during an orthopedic hand surgery.

A virtual boundary associated with a restricted access area may be adjusted based on one or more conditions. For example, as described herein, a virtual boundary for a radioactive device and/or a high energy imaging equipment may be adjusted, e.g., based on a power level and/or an imaging focus to minimize an inadvertent exposure to an HCP in an OR. The virtual boundary area may be based on a physical boundary of the equipment, a size of an OR, and/or an energized state (e.g., power level) of the instrument.

A virtual boundary associated with a restricted access area may be adjusted based on a surgical step and/or an infection possibility. For example, when performing an intubation or extubation, a patient may have a virtual boundary area generated around an area of a head and/or shoulders of the patient. The virtual boundary area may be small and/or contained by a filtration system during a surgical procedure, such as a Bronchoscope procedure. During intubation or extubation, the virtual boundary area may be adjusted. For example, during intubation or extubation, the virtual boundary area may be adjusted, e.g., adjusted to be larger due to a likelihood of aerosol from breathing contaminating a larger zone. The virtual boundary around the head and/or shoulders area of the patient may include an adaptive virtual boundary area. For example, the adaptive virtual boundary around the patent area may be adjusted dynamically and may be adjusted (e.g., reacted) as the patient coughs or forcibly expels air, and aerosol and the virtual boundary area may be adjusted by expanding the restricted area.

The computing system may notify HCPs in the OR if the adaptive virtual boundary area for the surgical instrument has been changed. For example, the computing system may notify HCPs that a virtual boundary area, e.g., an adaptive virtual boundary area, for the surgical instrument has been changed. The computing system may monitor the authorized HCPs in the virtual boundary area for exposure levels and/or verify against PPE that the HCPs are using are proper.

A virtual boundary area may be illustrated by using a laser light. HCPs in an OR may see the laser light and visually recognize where the virtual boundary areas in the OR are located. The virtual boundary areas may have different colors to represent different types of virtual boundary areas. For example, a constant virtual boundary area may have different laser color than a selective and/or an adaptive virtual boundary areas. A different later light may provide information about a danger level, a power level, and/or the like associated with a virtual boundary area.

A virtual boundary area may be defined by a layout of an OR, a location/position of a surgical instrument, and/or an equipment area in an OR. As described herein, a virtual boundary area may be adjusted based on a movement of a surgical instrument and/or an equipment during a surgical procedure. A virtual boundary area may be adjusted based on reposition of a patient (e.g., moving the patient to the sides) or reposition of an OR table and a sterile surgical tray table.

The computing system may send a notification to an unauthorized HCP when the computing system determines that the unauthorized HCP is approaching, is in a proximity to, and/or near a virtual boundary associated with a restricted access area in an OR. The computing system may send a notification to an authorized HCP regarding a boundary interaction, e.g., to ensure safety of the HCP. For example, the computing system may send a notification to an authorized HCP before and/or after entering and exiting the virtual boundary. The notification to the HCP (e.g., the authorized and/or unauthorized HCPs) may prevent accidental or inadvertent interaction with the virtual boundary area.

As described herein, the computing system may send a notification to an HCP within a virtual boundary of a restricted access area or upon approaching the virtual boundary area. The computing system may use one or more of a haptic notification, a visual notification, an audible notification, a visuo-haptic notification. The notification may be or may include a modality and/or feedback. The notification may provide a warning, provide awareness about a surrounding, such as a location of a virtual boundary of a restricted access area, prevent a collision others or equipment, such as a sterile area, and/or an indication if an individual is near or violate a controlled area or boundary.

The computing system may provide a visual feedback. The computing system may provide a visual indicator and display a virtual boundary of a restricted access area or zone within an OR. The computing system may utilize a laser projector to project (e.g., outline) a virtual boundary of a restricted area or zone on a floor, on a wall, and/or within an OR. For example, the computing system may use a laser projector to provide a visual indication of a virtual area and/or zone to an HCP in an OR. The computing system may use different colors to represent different virtual boundaries associated with the restricted areas/zones. For example, the computing system may use a blue color to indicate a virtual boundary for a sterile field area, an orange color for a virtual boundary for a high energy equipment, a purple color for a virtual boundary for an anesthesiologist equipment, and/or the like. The computing system may change the color of the lights when an unauthorized HCP is approaching the virtual boundary of a restricted access area. For example, the computing system may turn the lights to yellow if an unauthorized HCP is near the virtual boundary of the restricted access area and turn the lights to red if the unauthorized HCP enters/interacts with the virtual boundary of the restricted access area.

The computing system may use one or more laser markings for virtual boundaries associated with restricted access areas/zones based on one or more of roles, permissions, certificates, etc., associated with HCPs in an OR. For example, a virtual boundary for a sterile area/zone may show a green color when an HCP with a correct authentication and/or an approved credential is near or within the virtual boundary. If an unauthorized HCP with an incorrect authentication and/or improper credential is near or within the virtual boundary, the computing system may use red color to provide a warning and/or an alert to the unauthorized HCP.

The computing system may generate a virtual boundary for a restricted access area, and the virtual boundary may be visible using an augmented reality (AR) device, such as AR glasses. For example, the computing system may generate colored zones as described herein and/or create laser lights onto a OR floor and HCPs may see the virtual boundaries using the AR devices.

The computing system may display an OR. For example, the computing system may display one or more of an OR, HCPs in the OR and movements of the HCPs in the OR, surgical equipment, and the like. The computing system may display one or more virtual boundaries of restricted access areas. The computing system may highlight the virtual boundary areas if an unauthorized HCP is approaching and/or interacting with the virtual boundary area. The computing system may provide a bird's eye overview of the OR to the HCPs in the OR. The OR display and the displayed information may enable an HCP, such as a surgeon, to reinforce one or more virtual boundary areas and/or override the virtual boundary areas that are highlighted.

The computing system may provide an audible feedback. The computing system may provide an audible tone or audible information to an HCP near or interacting with a virtual boundary of a restricted access area. For example, the computing system may broadcast audible information about a virtual boundary area as an authorized HCP is approaching the boundary area or if an unauthorized HCP is approaching or interacting with the virtual boundary area. The computing system may provide different tones based on a defined virtual boundary area. For example, the computing system may have different tones for a virtual boundary for a sterile field area, a virtual boundary for a patient area, a virtual boundary for an equipment area, a virtual boundary for a critical area.

The computing system may provide different tone level based on different virtual boundary areas and/or closeness of an HCP to the virtual boundary area. For example, if an unauthorized HCP is approaching a virtual boundary area, a computing system may provide a short quiet audible feedback to the HCP. As the unauthorized HCP is getting closer to the virtual boundary area, the audible feedback may be a long and louder audible feedback (e.g., increasing a level of the audible feedback). The computing system may provide the audible feedback to a corresponding HCP, e.g., via a device associated with the HCP. If the computing system is broadcasting the audible feedback in the OR, the computing system may noise-cancel the audible feedback to other HCPs, e.g., to minimize distraction.

The computing system may provide a haptic feedback. An HCP may be wearing one or more devices, such as a phone, a smart watch, a smart tracker may. For example, an HCP may be wearing a device on a wrist and/or an ankle (e.g., glove, hand, shoes, feet, etc.). The HCP may wear the device that may have wrist and/or ankle bands on each extremities. The computing system may provide a haptic feedback to an extremity that is at risk for contacting a virtual boundary for a restricted access area. For example, if a left foot of an unauthorized HCP is near a virtual boundary for a sterile field area, the computing system may send a haptic feedback to a device that is on a left ankle of the unauthorized HCP. The computing system may send the haptic feedback to the left ankle device and provide a notification that the HCP may not step or walk in that direction (e.g., left direction).

The computing system may provide a different level of a haptic feedback. The computing system may increase or decrease a level of a haptic feedback as an HCP is closing to and/or approaching or moving away from a virtual boundary of a restricted access area. For example, if an unauthorized HCP is approaching a virtual boundary of a restricted access area, the computing system may increase an intensity of a haptic feedback and/or increase a pulse of a haptic feedback. If the unauthorized HCP is moving away from the virtual boundary of the restricted access area, the computing system may decrease the intensity of the haptic feedback and/or decrease the pulse of the haptic feedback.

If the computing system determines that an unauthorized HCP is ignoring a haptic feedback to a particular device (e.g., to a left ankle device), the computing system may send a haptic feedback to one or more devices that the unauthorized HCP is wearing.

The computing system may combine one or more feedbacks described herein and may provide a visuo-haptic mixed reality (VHMR).

A computing system may monitor an HCP and may determine an access authorization for the HCP. For example, the computing system may determine an acceptability of crossing a virtual boundary of a restricted access area. The computing system may detect an environmental parameter and/or a personal parameter, e.g., to determine acceptability to crossing a virtual boundary area. For example, the computing system may detect an environmental parameter and/or a personal parameter based on one or more of a credential, a certificate, and/or other access control level information associated with an HCP.

The computing system may perform aseptic monitoring of an HCP. For example, if the computing system determines that an HCP passes an aseptic test, the computing system may allow the HCP to enter a virtual boundary of a restricted access area. If the computing system determines that an HCP fails an aseptic test, the computing system may revoke an access authorization associated with the HCP and disallow the HCP from entering a virtual boundary of a restricted access area.

As a surgery carries a risk of infection, an HCP in an OR may receive an extensive education in a technique to prevent a surgical infection. For example, an HCP in an OR (e.g., such as a surgeon or a scrub nurse) may be aware of how to properly wear and remove a sterile protective equipment, such as a gown and/or gloves, how to scrub hands to decrease a risk of bacterial contamination, and/or how to manage a surgical instrument/tool to prevent contamination of a sterile instruments or dressings. A circulating nurse, who does not wear a full sterile protective equipment (e.g., less sterile protective equipment than a scrub nurse and/or a surgeon), may be unauthorized to enter a virtual boundary of a restricted access area, such as a sterile area in an OR. The computing system may monitor a movement of a circulating nurse in the OR and prevent the circulating nurse from entering or interacting with the virtual boundary of a sterile field area and prevent from contaminating the sterile area around an operating table.

The computing system may monitor an HCP. For example, the computing system may monitor an HCP for pre-surgery and post-surgery, e.g., to verify that a necessary step has been completed. If the computing system determines that an HCP has failed to complete a step, such as a proper scrubbing before entering an OR or after performing the surgery, the computing system may send a notification to the HCP and/or revoke an access authorization for the HCP. The computing system may revoke an access authorization for the HCP temporarily, e.g., until the step has been completed.

The computing system may monitor an equipment during a surgery. For example, the computing system may monitor a surgical glove from any sign of breaking or monitor a surgical gown for a tear. If the computing system detects a tear or break, the computing system may send a notification to the HCP to replace the equipment.

The computing system may monitor battery transfer to a surgical device. For example, a battery pack (e.g., a lithium and/or lithium-ion battery pack) for a surgical device may not be sterilized. The battery pack may have an embedded RFID chip that tracks an aseptic transfer. For example, the battery pack may enter into an OR for a surgery. The computing system may receive an alert from the battery pack (e.g., via a RFID beacon), and the computing system may identify the batter pack entering the OR. The computing system may track the battery pack and send a notification to an HCP based on a virtual boundary of a restricted access area in the OR.

The computing system may monitor a procedure step associated with the battery back. If a procedure step has been missed or done incorrectly, the computing system may alert an HCP about a potential issue.

The computing system may identify a virtual boundary of a restricted access area for a surgical instrument. A surgical instrument may be able to perform a surgical step using a high energized state. The computing system may detect an energized state associated with a surgical instrument during a surgical procedure. The computing system may identify a surgical step of an operation. For example, the computing system may identify a surgical step based on surgical monitoring data. The surgical step may be or may include a current surgical step or an upcoming surgical step.

Based on the identified surgical step and the detected energized state, the computing system may adjust a virtual boundary area of the surgical instrument. For example, if the computing system detects that the surgical instrument is in a high energized state and matches with the surgical step, the computing system may adjust the virtual boundary of the surgical instrument, e.g., by increasing the virtual boundary area. If the computing system detects that the energized state is above a threshold level, the computing system may increase the virtual boundary area for the surgical instrument. If the computing system detects that the energized state is below the threshold level, the computing system may decrease the virtual boundary area for the surgical instrument.

If the computing system determines that the surgical instrument is in a high energized state but does not match with the surgical step, e.g., if an anomaly exists, the computing system may adjust the virtual boundary area of the surgical instrument. For example, the computing system may increase the virtual boundary area of the surgical instrument if the computing system detects that the surgical instrument has a high energized state when the current step of the surgical procedure does not need the surgical instrument to be turned on and/or be in use. The computing system may send a notification to an HCP, e.g., to prevent inadvertent contact with the surgical instrument.

FIG. 23 illustrates an example notification of a computing system for an unauthorized energy level change of a surgical instrument. As illustrated in FIG. 23 , the computing system may identify one or more virtual boundaries of restricted access areas in an OR 36400. The one or more virtual boundaries of restricted access areas in the OR may include a virtual boundary area for an anesthesiologist area 36420, a virtual boundary area for an operation table area 36410, a virtual boundary area for a surgical instrument area 36415, and/or a virtual boundary area for an operation area of a patient 36425. As described herein, the computing system may monitor a movement of an HCP in an OR. The computing system may determine whether the HCP has an access authorization to enter, exit, interact with, or be in a virtual boundary of a restricted access area in the OR. The computing system may determine an access authorization of an HCP based on one or more of an HCP role during a surgical procedure, an assignment associated with the HCP during the surgical procedure, a PPE associated with the HCP, a biomarker measurement associated with the HCP, or a restricted area type.

The computing system may monitor an energy level of a surgical instrument in an OR. If the computing system detects a change in the energy level of a surgical instrument, the computing system may determine that the energy level has been changed by an authorized HCP. If the computing system determines that the energy level has been changed by an unauthorized HCP who entered the virtual boundary area for a surgical instrument 36415, the computing system may send a notification. The computing system may send a notification to a display 36405 and notify other HCPs that the unauthorized HCP has inadvertently changed the energy level of the surgical instrument. The computing system may send a notification to the display 36405 and/or to the unauthorized HCP indicating that the HCP does not have an authorization to be in a proximity to or within the virtual boundary for the surgical instrument 36415.

If another HCP, such as a surgeon, sees the notification about the unauthorized HCP and/or the unauthorized energy level change by the unauthorized HCP, the surgeon, e.g., a lead surgeon, may adjust the access authorization associated with the unauthorized HCP. For example, the unauthorized HCP may be another surgeon who is assisting the lead surgeon. The assistant surgeon may have an access authorization to be in the virtual boundary for the operation table area 36410. The assistant surgeon may not have an access authorization to enter or be within the virtual boundary area for the surgical instrument 36415. The lead surgeon may adjust the access authorization of the assistant surgeon. For example, the lead surgeon may adjust the access authorization of the assistant surgeon after seeing the notification on the display 36405 and may allow the assistant surgeon to enter or be in the virtual boundary area for the surgical instrument 36415.

Another HCP may adjust the access authorization of the unauthorized HCP based on an emergency situation. For example, during an emergency where a lead surgeon needs additional hand to operate a surgical instrument, the lead surgeon may adjust an access authorization of an assistant surgeon to enter or be in a virtual boundary area for a surgical instrument 36415 as described herein.

A computing system may identify an equipment, such as a surgical instrument, associated with a surgical procedure in an OR. For example, the computing system may download a surgical plan created by an HCP for a pre-op procedure and may identify one or more surgical instruments to be used for a surgical procedure. The computing system may detect a control input by an HCP to control the surgical instrument. The control input by an HCP may be turning on or turning off the surgical instrument. The control input by an HCP may be adjusting an energy level of the surgical instrument. The control input by an HCP may be adjusting a position of the surgical instrument.

The computing system may determine the HCP's access control level associated with the surgical instrument. For example, an access control level associated with the HCP may include whether the HCP has an authorization to control the surgical instrument. The access control level associated with an HCP may be tiered. For example, a tiered access control level (e.g., a first tiered access control level) may be turning on or turning off the surgical instrument. Another tiered access control level (e.g., a second tiered access control level) may be adjusting an energy level of the surgical instrument. For example, the second tiered access control level associated with adjusting an energy level of a surgical instrument may be a higher tier than the first tired access control level associated with turning on or off the surgical instrument.

The computing system may determine whether to effectuate the detected control input by the HCP. The computing system may determine whether to effectuate the control input by the HCP based on the access control level associated with the HCP. If the computing system determines that the HCP is authorized to control the surgical instrument (e.g., HCP is authorized to effectuate the control input to control the surgical instrument) based on the access control level, the computing system may effectuate the control input by the HCP to control the surgical instrument. If the computing system determines that the HCP is unauthorized to control the surgical instrument (e.g., the HCP is unauthorized to effectuate the control input to control the surgical instrument) based on the access control level associated with the HCP, the computing system may block the control input by the HCP to control the surgical instrument.

The computing system may send an alert to a device associated with the HCP if the computing system blocks the control input by the HCP attempting to control the surgical instrument. The alert may be or may include a notification to the HCP, notifying that the control input by the HCP has been blocked and/or the access control level information associated with the HCP. The computing system may send an alert to a display in the OR. For example, as illustrated in FIG. 23 , the computing system may send an alert to a display 36405 in an OR. The alert may indicate that the control input by the HCP has been blocked.

The computing system may be or may include an HCP monitoring system such as the HCP monitoring system 20000, 20002, 20003, or 20004 as described herein with respect to FIGS. 1-3 . The computing system may be a computing system operatively connected to the HCP monitoring system(s) 20000, 20002, 20003, and/or 20004. The computing system may be or may include the computing system 20271 described herein with respect to FIG. 9 . The computing system may be or may include the computer system 20063 described herein, for example, with respect to FIG. 4 . The computing system may be or may include the computing system 20064 described herein, for example, with respect to FIG. 4 . The computing system may be or may include the surgical hub 20006 as described herein with respect to FIGS. 1-3 , surgical hub system 20060 in FIG. 4 , the computer-implemented interactive surgical system 20070, in FIG. 5 , the surgical hub or computing device 20243 in FIG. 7 , the surgical hub 20270 in FIG. 9 , the console 20294 in FIG. 10 , and/or the surgical hub 5104 in FIG. 11 . For example, the computing system may obtain surgical monitoring data associated with one or more surgical procedures. The surgical procedures may take place in an OR or multiple ORs.

As described herein, the computing system may monitor a movement of an HCP. The computing system may determine that the HCP is in a proximity to an operating table. The computing system may determine that the HCP is unauthorized to control a surgical instrument, e.g., based on an access control level associated with the HCP. The computing system may send an access control level adjustment message to another HCP, such as a surgeon. The access control level adjustment message may inquire whether the access control level associated with the HCP needs an adjustment based on the proximity of the HCP to the operating table. The computing system may receive an access control level adjustment request from another HCP, such as the surgeon. The access control level adjustment request may indicate a change to the access control level associated with the HCP. The computing system may adjust the access control level for the HCP based on receiving the access control level adjustment request from another HCP. As described herein, the access control level adjustment request may allow the HCP to control the surgical instrument (e.g., turn on/off the surgical instrument and/or adjust an energy level associated with the surgical instrument). The computing system may send an access control level adjustment notification to the HCP. The computing system may send the access control level adjustment notification to the display in the OR. The access control level adjustment notification may indicate the HCP who authorized the access control level change (e.g., by a surgeon).

The computing system may adjust a control access level for a surgical instrument associated with an HCP based on a surgical step in a surgical procedure. The computing system may identify a current surgical step. Based on the current surgical step, the computing system may determine whether to adjust the access control level associated with the HCP. For example, at an initial step of a surgical procedure, a control access level for a surgical instrument associated with a surgeon may be turning on or turning off the surgical instrument. If the surgeon attempts to adjust an energy level associated with the surgical instrument at the initial step of the surgical procedure, the computing system may block the control input by the surgeon.

The computing system may adjust the access control level associated with the HCP to allow the HCP to control the surgical instrument associated with the current surgical step in the surgical procedure. For example, the computing system may determine that the current surgical step involves using the surgical instrument to make an incision. The computing system may adjust the control level of the surgeon. The surgeon may adjust the energy level of the surgical instrument and may be able to make the incision, e.g., by adjusting from a low energized state to a high energized state of the surgical instrument.

After the HCP has completed the current surgical step, the computing system may readjust the access control level associated with the HCP that matches with an upcoming surgical step. For example, after the surgeon has made the incision for the current surgical step and the computing system determines that an upcoming surgical step does not involve a high energized stage of the surgical instrument, the computing system may readjust the access control level associated with the HCP to block a control input of the surgeon, e.g., to increase or to maintain the high energized level of the surgical instrument.

The computing system may adjust an HCP's access control level associated with an instrument based on an energized state of the instrument. The computing system may identify an energized state of a surgical instrument. If the computing system identifies that the surgical instrument has a high energized state, the computing system may adjust access control level of the HCP and block the control input by the HCP to control the surgical instrument. For example, to prevent an inadvertent control of the surgical instrument, the computing system may block a control input by a scrub nurse when the computing system determines that the surgical instrument is in a high energized state.

If the computing system identifies that the surgical instrument has a low energized state or turned off, the computing system may adjust the access control level of the HCP and effectuate the control input by the HCP to control the surgical instrument. For example, the computing system may allow a scrub nurse to turn on or turn off the surgical instrument when the computing system determines that the surgical instrument is in a low energized state or is turned off.

The computing system may adjust a control access level of an HCP based on biomarker measurement(s) associated with the HCP. A biomarker associated with an HCP may be or may include one or more of a fatigue level, a stress level, or an amount of time the HCP has been operating. The computing system may monitor a biomarker associated with an HCP, such as a surgeon. The computing system may determine whether to adjust the access control level associated with the HCP based on the monitored biomarker of the HCP. If the biomarker associated with the HCP indicates that the HCP has an increased fatigue level, an increased stress level, or an exceeded threshold operating hour, the computing system may block a control input from the HCP to control the surgical instrument. The computing system may send an alert to the HCP, indicating the increased fatigue level, the increased stress level, or the exceeded threshold operating hour.

If the biomarker associated with the HCP indicates that the HCP has a decreased fatigue level, a decreased stress level, or a below threshold operating hour, the computing system may effectuate a control input from the HCP to control the surgical instrument. The computing system may send an alert to the HCP indicating a current fatigue level, a current stress level, or a current operating hour associated with the HCP.

In examples, the computing system may receive measurement data associated with an HCP from a sensing system. Based on the measurement data, the computing system may determine an elevated fatigue level associated with an HCP. The measurement data may indicate an HCP, such as a surgeon, may take too long (e.g., longer than a threshold time) to a change in input, which may be referred to as over-correction, for a perceived mistake. The computing system may interpret repeated correction, over-correction, or oscillating reaction as an indicator of fatigue and/or elevated fatigue level associated with the HCP. For example, based on biomarker measurements of an HCP, the computing system may determine a value associated with hydration/dehydration of the HCP. Dehydration may impact energy levels and make a person feel tired and fatigued. Less body fluid tends to increase heart rate. The computing system may analyze heartbeat data in the context of hydration levels and differentiate between stress and other heart elevation events from hydration. The computing system may employ a baseline measure to differentiate acute events from ongoing chronic events and to differentiate between fatigue and dehydration.

In examples, the computing system may receive measurement data from a sensing system associated with an HCP in an OR (e.g., a sensing system associated with a surgeon). The measurement data may indicate that the HCP has an increased stress level. For example, an increased stress level may be indicated by change in a heart rate of the HCP, e.g., from a base value. The computing system may derive/infer an increased stress level of the HCP by cross-referencing the receipt of data from the corresponding sensing system.

An HCP's fatigue level may be measured/determined based on instrument usage data, for example. The computing system may calculate a weighted measure of fatigue for the HCP operating the surgical instrument as well as others in the operating room. The weighted measure of fatigue may be based on cumulative cooperative events and contributions. For example, the weighted measure of fatigue may be based on the intensity of stress experienced by an HCP and the force exerted by the HCP over time in controlling an actuator such as closure trigger over time.

Details on energy level and fatigue level measurements are described in U.S. application Ser. No. 17/156,287 (attorney docket number END9290USNP1), titled METHOD OF ADJUSTING A SURGICAL PARAMETER BASED ON BIOMARKER MEASUREMENTS, filed Jan. 22, 2021, the disclosure of which is herein incorporated by reference in its entirety.

As described herein, the computing system may adjust and/or limit a control input by an HCP to control a surgical instrument. For example, the computing system may limit a control input by an HCP to control a surgical instrument based on a permission, such as an access control level and/or a proximity to a virtual boundary of a restricted access area, such as a sterile field, an operating table, or other HCP such as a surgeon.

The computing system may adjust a control input by an HCP attempting to control the surgical instrument based on a certification associated with an HCP. For example, the computing system may use a certification associated with an HCP to determine whether the HCP has a permission to make a control input and/or change a setting for a surgical instrument. Based on the certification and/or the permission, the computing system may effectuate or block the control input by the HCP.

The computing system may limit and/or adjust a control input of an HCP to an equipment based on a certification associated with an HCP. The computing system may identify a predefined set of equipment and/or a control associated with the identified equipment, e.g., based on a certification associated with an HCP. The computing system may monitor a control input by an HCP, e.g., to prevent an inadvertent adjustment and/or control of an equipment that an HCP is certified to interact with and/or to control an equipment.

For example, an anesthesiologist may have a certification to control (e.g., full control) an anesthesiology equipment. Other HCPs may have a partial control of an anesthesiology equipment. For example, an anesthetist nurse and/or an anesthesiologist resident may have a partial control of an anesthesiology equipment. Based on a certification associated with an HCP, the computing system may allow or block the HCP to control an equipment. For example, the computing system may determine, e.g., based on the certification associated with the anesthesiologist, that the anesthesiologist is allowed to control a setting and/or have a control interaction for an anesthesiology equipment, such as a sedation and/or a respiration equipment.

Based on a certification associated with other HCP, such as a scrub nurse, the computing system may determine that a scrub nurse does not have a permission to control a setting and/or have a control interaction for an anesthesiology equipment. If the computing system determines that an HCP does not have a permission to control or adjust a setting for an anesthesiology equipment, the computing system may block a control input by the HCP and prevent an inadvertent adjustment of the equipment by the HCP who is not certified to interact with and/or control the equipment.

The computing system may receive an override request from another HCP, such as a surgeon or an anesthesiologist. For example, a surgeon may override (e.g., override a lockout) a control input and/or an adjustment setting of an equipment, e.g., to distinguish between an inadvertently adjustment and an intention or an emergency adjustment of an equipment.

In examples, throughout a surgical operation, one or more surgical instruments may be used. The surgical instruments may need a form of energy to apply a therapeutic treatment and/or have an electromechanical control to function the surgical instrument. An example of a surgical instrument may be a laparoscopic device. The surgical instrument may be used multiple times throughout the surgical operation. The surgical instrument may be placed on/off a surgical table, handed-off to other HCPs, and/or disposed after the surgical operation.

The computing system may limit and/or adjust a control input by an HCP, e.g., based on a confirmation. For example, the computing system may limit and/or adjust a control input by an HCP based on a visual confirmation. The computing system may detect an inadvertent control input based on a visual confirmation and prevent energy applied to motor power of a surgical instrument. The computing system may effectuate a control input if the computing system determines that the control input is from hands of and/or is activated by an authorized HCP with a proper (e.g., correct) certification having a permission.

As described herein, the computing system may generate a virtual boundary of a restricted access area for a target surgical zone and limit control input by an HCP to control a surgical instrument. For example, the computing system may effectuate a control input by an authorized HCP in a virtual boundary of a target surgical zone and prevent inadvertent control and/or prevent injuring other HCP or a patient.

The computing system may adjust an access control level associated with an HCP based on a proximity to other HCP, such as in a presence of a surgeon. For example, the computing system may determine that a scrub nurse or an associate may be unauthorized to operate a circular stapler. The computing system may determine that the scrub nurse or the associate may be in a proximity to or in a virtual boundary of a restricted access area of a surgeon. If the computing system determines that the scrub nurse or the associate is in the proximity to or in the virtual boundary of a surgeon area, the computing system may adjust the access control level associated with the scrub nurse or the associate. The computing system may effectuate a control input by the scrub nurse or the associate, e.g., turning on the circular stapler.

The computing system may be aware of and/or identify a surgical step of a surgical operation. For example, the computing system may identify that a surgery has been completed and/or a surgical instrument is no longer needed for the surgical operation. If the computing system determines that the surgery is completed, the computing system may monitor for an activation of the surgical instrument and/or be in a powered state. If the computing system determines that the surgical instrument has been activated and/or is in a high energized state or is turned on, the computing system may block a control input by an HCP, e.g., to prevent inadvertently activating the surgical instrument while the HCP is cleaning up and/or disposing the instrument.

If the computing system determines that a surgery has been completed and a surgical instrument is a battery-operated device, the computing system may begin an energy removal step, e.g., using a draining circuit of the battery-operated device. The computing system may limit (e.g., block) a control input by an HCP during the energy removal step.

The computing system may adjust and/or limit a control input by an HCP for gas system. During a surgical operation in an OR, medical air, oxygen, carbon dioxide, nitrogen, nitrous oxide, and/or other gases may be supplied. If the computing system detects a control input to turn on/off or increase/decrease gases supplied during an operation, the computing system may determine an access control level of the HCP making the control input to control the device for supplying the gases. The computing system may determine a surgical step and confirm that the gas needs to be turn on/off or increase/decrease. If the computing system determines that the HCP has the access control level to adjust the gas level and the HCP's control of gas matches with the current surgical step, the computing system may effectuate the control input by the HCP. If the computing system determines that the HCP does not have the access control level and/or use of gas does not match with the current surgical step, the computing system may block the control input by the HCP. The computing system may send an alert to the HCP as described herein.

The computing system may control an energized state of a device. The computing system may control an energized state of a device, such as a device for radiology, based on the location of the HCP, the virtual boundary of a restricted access area, whether the HCP is wearing appropriate PPE, a threshold exposure time, the biomarker measurement(s) of the HCP, the biomarker measurement(s) of the patient, and/or the like. As described herein, the computing system may control the energized state of a device and effectuate control input by the HCP to control the device, upon determining that the HCP is in a proximity to a patient (e.g., within a virtual boundary of a patient, a surgical table, and/or a surgeon) and within the surgical area.

The computing system may monitor/determine whether an HCP, such as a radiologist or a radiologist tech is wearing a proper PPE. If the computing system determines that the HCP is not wearing a proper PPE, the computing system may block a control input by the HCP and send an alert. Examples of a proper PPE may be or may include one or more of a lead apron, lead glasses, a lead shield, and/or the like.

The computing system may monitor/determine whether an HCP is in a proper distance, such as an acceptable clearance, from the radiology device. If the computing system determines that the HCP is not in a proper distance, e.g., in an exposure area, the computing system may block a control input by the HCP and send an alert.

The computing system may monitor/determine an exposure time of an HCP to a radiology device. For example, if the computing system determines that the HCP exceeds a threshold exposure time, the computing system may block a control input by the HCP and send an alert.

The computing system may monitor/determine a biomarker associated with an HCP or a patient. For example, if the computing system determines that an HCP has an increased fatigue level and/or an increased level, the computing system may block a control input by the HCP and send an alert. The computing system may monitor a biomarker associated with a patient. If the computing system determines that a biomarker associated with the patient has suddenly changed, e.g., an emergency or a complication happened, the computing system may block a control input by the HCP and send an alert. The computing system may determine a type of patient based on the biomarker associated with the patient. For example, the computing system may determine that the patient is a pediatric patient or a pregnant patient. To minimize an exposure to a radiology, the computing system may block or adjust the control input by the HCP and send an alert.

FIG. 24 illustrates an example flow 36450 of monitoring an HCP movement relative to a virtual boundary of restricted access area in an OR as described herein. For example, at 36455, a computing system may determine a virtual boundary associated with a restricted access area. The computing system may be or may include the surgical hub 20006 as described herein with respect to FIGS. 1-3 , surgical hub system 20060 in FIG. 4 , the computer-implemented interactive surgical system 20070, in FIG. 5 , the surgical hub or computing device 20243 in FIG. 7 , the surgical hub 20270 in FIG. 9 , the console 20294 in FIG. 10 , and/or the surgical hub 5104 in FIG. 11 . The virtual boundary may be or may include a virtual boundary associated with a restricted access area for an anesthesiologist 36005, 36105, a virtual boundary area associated with a restricted access area for a surgeon 36025, 36115, a virtual boundary associated with a restricted access area for a surgical table 36030, 36120, a virtual boundary associated with a restricted access area for a scrub nurse 36035, 36125, a virtual boundary associated with a restricted access area for a circulating nurse 36040, a virtual boundary associated with a restricted access area for a surgical instrument, a sterile tray table, and/or other surgery related equipment 36045, 36050, 36055, 36060, 36065, a virtual boundary associated with a restricted access area for an observer 36135, a virtual boundary associated with a restricted access area for an SSC 36140, a virtual boundary associated with a restricted access area for an assistant, a virtual boundary associated with a restricted access area for an anesthesia nurse 36110, described herein with respect to FIGS. 19-20 .

At 36460, the computing system may identify an HCP in an OR. At 36465, the computing system may monitor a movement of the identified HCP. For example, the computing system may determine whether an HCP is in a proximity to a virtual boundary associated with a restricted access area. The computing system may determine that the HCP is about to interact with (e.g., enter, exit, or leave) the virtual boundary associated with a restricted access area.

At 36470, the computing system may determine that the HCP has an access authorization to interact with or enter/exit the virtual boundary associated with a restricted access area as described herein. At 36475, the computing system may send a notification to the HCP. For example, if the computing system determines that the HCP is in a proximity to the virtual boundary associated with a restricted access area (e.g., based on the monitored movement of the HCP in 36465) and if the computing system determines that the HCP is unauthorized to interact with or enter/exit the virtual boundary associated with a restricted access area (e.g., based on the determination of the HCP access authorization in 36470), the computing system may send a notification to the HCP indicating that the HCP is unauthorized to enter the virtual boundary. If the computing system determines that the HCP is in a proximity to the virtual boundary associated with a restricted access area (e.g., based on the monitored movement of the HCP in 36465) and if the computing system determines that the HCP is authorized to interact with or enter/exit the virtual boundary associated with a restricted access area (e.g., based on the determination of the HCP access authorization in 36470), the computing system may skip sending a notification to the HCP.

FIG. 25 illustrates an example flow 36500 of control access verification of an HCP in an OR, which may be performed at the computing system described herein. The computing system may be or may include the surgical hub 20006 as described herein with respect to FIGS. 1-3 , surgical hub system 20060 in FIG. 4 , the computer-implemented interactive surgical system 20070, in FIG. 5 , the surgical hub or computing device 20243 in FIG. 7 , the surgical hub 20270 in FIG. 9 , the console 20294 in FIG. 10 , and/or the surgical hub 5104 in FIG. 11 .

At 36505, the computing system may identify a surgical instrument associated with a surgical procedure. For example, as described herein, the computing system may download a surgical plan generated by an HCP during a pre-op procedure. The computing system may identify one or more surgical instruments to be used for a surgery and identify one or more instruments to be used for the surgical procedure.

At 36510, the computing system may detect a control input by an HCP. For example, as described herein, the control input may be turning on/off a surgical instrument or change an energized state of the surgical instrument (e.g., from a low energized state to a high energized state or from the high energized state to the low energized state).

At 36515, the computing system may determine that an access control level of the HCP to control the surgical instrument. For example, the computing system may determine whether the HCP has an access control authorization to control the surgical instrument.

At 36520, the computing system may determine whether to effectuate the control input by the HCP. For example, if the computing system determines that the HCP has an access control authorization to control the surgical instrument, the computing system may effectuate the control input by the HCP to control the surgical instrument. If the computing system determines that the HCP is unauthorized to (e.g., does not have the access control authorization) to control the surgical instrument, the computing system may block the control input by the HCP.

A computing system may monitor an HCP or an equipment based on a location within an OR and/or an exposure time in a virtual boundary of a restricted access area. The computing system may determine, based on a local recording, how long an HCP has been in an OR and/or how long a device has been in an OR. For example, the computing system may determine who long a battery-operated devices (ENDO) has been set up in an OR The battery-operated device may have a shelf life of 12 hours once the device has been set up and battery is installed. The computing system may determine that the battery-operated device may not have an optimum performance if the battery-operated device has been set up more than the shelf life.

The computing system may monitor/determine an exposure time in an OR for a device. As a device may have a specific life after the device has been set up, the computing system may send an alert to an HCP, e.g., to replace the device.

The computing system may track a location of a device within an OR. For example, the computing system may record a movement of the device within an OR and/or between virtual boundaries of restricted access areas, an interaction of the device with an HCP, and/or the like.

FIG. 26 illustrates a flow diagram of example processing associated with monitoring an operating room and determining parameters associated operating room systems. As shown, at 37110, an HCP monitoring system, which may be an HCP monitoring system 20002, 20003, or 20004 as described herein with respect to FIGS. 1-3 , may monitor data. The HCP monitoring system may monitor data associated with an OR. The monitored data may include data associated with one or more surgical procedures. The surgical procedures may take place in an OR or multiple ORs. The monitored data may include data associated with a HCP, a patient, a surgical instrument, surgical equipment, and/or a surgical device. The surgical device may include a surgical access device. The monitored data may include data associated with positioning.

The HCP monitoring system may include an OR room imaging system. The HCP monitoring system may include one or more sensing systems. The one or more sensing systems may be surgeon sensing systems 20020 as described herein with respect to FIG. 2 . The surgeon sensing systems may be worn by HCPs. The surgeon sensing systems may monitor biomarkers associated with the HCPs. The one or more sensing systems may include a patient sensing system. The patient sensing system may be worn by the patient, for example. The patient sensing systems may monitor biomarkers associated with the patient.

The HCP monitoring system may comprise one or more environmental sensing systems for sensing one or more environments such as, for example, the environment in an OR. The environmental sensing systems may comprise one or more environmental sensing systems 20015 such as, for example, those described above in connection with FIGS. 1-10 . The environmental sensing system may include a camera, which may be the set of cameras 20021 as described herein in FIG. 2 . The environmental sensing system may include a microphone, which may be the set of microphones 20022 as described herein in FIG. 2 . The environmental sensing system may include other sensors that may be deployed in the operating room. For example, the environmental sensing systems may include one or more of a camera, a microphone, and other sensors that may be deployed in the operating room. For example, the HCP monitoring system may include one or more OR room imaging systems, surgeon sensing systems, patient sensing systems, or environmental sensing systems.

The HCP monitoring system may include RF systems. The RF systems may be smart and self-identifying. For example, RFID tags may be used. RFID tags may be used to identify HCPs. RFID tags may be used to determine an HCP location. RFID tags may be used to identify a surgical instrument. RFID tags may be used to identify a surgical instrument location.

The HCP monitoring system may monitor data associated with an HCP within an OR. The HCP monitoring system may monitor data associated with an HCP positioning within an OR. The monitored data associated with an HCP positioning may include a location of an HCP within the OR. The monitored data associated with an HCP positioning may include a posture of an HCP. The monitored data associated with an HCP positioning may include a characteristic of an HCP, such as a height, an arm length, a hand shape, a hand length, a waist width, a shoulder width, an age, and the like, for example. The monitored data associated with an HCP positioning may include a head or eye position of an HCP. The head or eye position of an HCP may include an angle of viewing, such as the direction an HCP is looking, for example.

The HCP monitoring system may monitor data associated with a patient within an OR. The HCP monitoring system may monitor data associated with a patient positioning within an OR. The monitored data associated with a patient positioning may include a characteristic of a patient, such as a height, a weight, a waist height, a shoulder height, and the like, for example. The monitored data associated with a patient positioning may include a patient position on a bed in the OR. The monitored data associated with a patient positioning may include a patient location within the OR. The monitored data associated with a patient positioning may include a patient location relative to an HCP location within the OR. The monitored data associated with a patient positioning may include a trocar location.

The HCP monitoring system may monitor data associated with surgical equipment within an OR. The surgical equipment may include surgical instruments, surgical devices, robotic surgical equipment, and the like. The surgical devices may include surgical access devices. The HCP monitoring system may monitor data associated with surgical equipment positioning within the OR. The HCP monitoring system may monitor data associated with an operating table, which may be the operating table 20024 as described herein with respect to FIG. 2 . The HCP monitoring system may monitor data associated with surgical tables and/or surgical trays, such as mayo stands, for example. For example, the HCP monitoring system may monitor data associated with movement of surgical instruments.

The HCP monitoring system may monitor data associated with a visual display. The HCP monitoring system may monitor data associated with a surgical display. For example, the monitored data may include data associated with visual display positioning. The data associated with visual display positioning may include a visual display location. The data associated with the visual display positioning may include a visual display angle. The data associated with the visual display positioning may include a visual display location and angle. The monitored data may include a display setting associated with the visual display. The display setting may include one or more of a brightness, color temperature, color contrast, or font associated with the visual display.

The HCP monitoring system may be adapted to perform object detection. The HCP monitoring system may perform object detection to track objects, for example, within an OR. Moving object detection may be performed to recognize the physical movement of a person or an object in a given place or region. By acting segmentation among moving objects and stationary area or region, the moving objects motion could be tracked and thus could be analyzed later. Moving object detection may be performed via background subtraction, frame differencing, temporal differencing, and or optical flow analysis.

The HCP monitoring system may use RF systems to locate HCPs and surgical equipment in the OR. The RF systems may be smart and self-identifying RF systems. HCPs, instruments, equipment, and/or boundaries may be located using spatial identifying sensors. The locations of HCPs, equipment and/or boundaries may be tracked with respect to the room and/or with respect to the patient, via wireless sensors and beacons. RFID tags may be affixed onto instruments and/or HCPs. A surgical instrument or HCP may be associated with a unique RFID identification. Based on the RFID tags, the location of surgical instruments and HCPs may be monitored and/or tracked.

The HCP monitoring system may monitor data associated with an OR before a surgical procedure. The HCP monitoring system may monitor location, movement, and/or orientation of various surgical equipment and HCPs in the OR. For example, a gyroscope or 3 axis accelerometers may be used to determine orientation and position.

The HCP monitoring system may record a surgical procedure, such as a laparoscopic procedure, for example. The HCP monitoring system may record a surgical procedure using a camera and/or a microphone.

At 37112, the HCP monitoring system may communicate the monitored data. The HCP monitoring system may communicate the monitored data to a surgical computing system, which may be, for example, a surgical hub 20006. The monitored data may be continuously gathered and communicated prior to and during a surgical procedure.

As shown at 37114, surgical equipment may monitor data. The surgical equipment may be a surgical instrument 20282 as described in connection with FIG. 10 . The surgical instrument 20282 may monitor data, such as user inputs associated with movement and positioning of the surgical instrument, for example. The surgical instrument 20282 may use an acceleration sensor to monitor the movement and positioning of the surgical instrument 20282. The surgical instrument 20282 may monitor the orientation of the surgical instrument 20282. The surgical instrument 20282 may monitor a length of time the surgical instrument 20282 is maintained in a particular positioning.

The surgical equipment may be or comprise a visual display. For example, the surgical equipment may be the primary display 20023 as described in connection with FIG. 2 . The primary display 20023 may monitor data, such as positioning, for example.

At 37116, the surgical equipment may communicate the monitored data. The surgical equipment may communicate the monitored data to a surgical computing system, which may be, for example, a surgical hub 20006. The monitored data may be continuously gathered and communicated prior to and during a surgical procedure.

At 37118, the surgical computing system may obtain monitored data which may comprise receiving monitored data. The surgical computing system may receive monitored data from the HCP monitoring system. The surgical computing system may receive monitored data from surgical equipment. The surgical computing system may receive monitored data from the HCP monitoring system and surgical equipment.

At 37120, the surgical computing system may process the received monitored data. The surgical computing system may determine one or more parameters based on the monitored data. The surgical computing system may receive monitored data associated with noise occurring in the operating room. The surgical computing system may determine, based on the monitored data associated with noise in the operating room, one or more parameters for controlling the operation of a display system or display monitor. The parameters may control the display to prioritize particular data on the display.

The surgical computing system may receive monitored data associated with the movements and/or positioning of a healthcare professional. The surgical computing system may determine, based on the monitored data associated with the movements and/or positioning of the healthcare professional, one or more parameters for controlling operation of a lighting system. The parameters may control the lighting system to direct light to an area that is a focus of the healthcare professional.

The surgical computing system may receive monitored data associated with air composition in the operating room. The surgical computing system may determine, based on the monitored data associated with air composition, one or more parameters for one or more air handling systems in the operating room. The parameters may control the air handling systems to adjust air flow, air pressure, and/or air filtration in the operating room.

The surgical computing system may receive monitored data associated with temperature of an individual or space in the operating room. The surgical computing system may determine, based on the monitored data associated with temperature, one or more parameters for one or more temperature control systems. The parameters may control the temperature control system to increase or decrease temperature at a particular location in the operating room.

The surgical computing system may receive monitored data associated with the noise occurring in the operating room. The surgical computing system may determine, based on the monitored data associated with noise in the operating room, a significance of a surgical process being undertaken. The surgical computing system may determine, based the monitored data and the significance of the surgical process being undertaken, one or more parameters for prioritizing display of information on a display.

At 37122, the surgical computing system may communicate the parameters to the appropriate systems associated with the operating room. For example, if the parameters are associated with control of a surgical device or surgical equipment, the parameters are communicated to that device. If the parameters are associated with an operating room system such as, for example, an operating room lighting system, or display system, the parameters are communicated to the appropriate operating room system.

At 37124, a surgical device or surgical equipment may receive parameters from the surgical computing system. The surgical device or surgical equipment may be any that may be controlled to modify operation. For example, the surgical equipment may be a surgical knife, a surgical robot, a surgical table, an operating bed, and the like.

At 37126, surgical equipment may modify its operation consistent with the received parameters. For example, a surgical table may have lighting capacity comprised therein. The received parameters may instruct the surgical table to modify the intensity of the lighting generated by the table. A surgical knife may have a vacuum feature comprised therein. The received parameters may instruction the surgical knife to increase the vacuum operation.

At 37128, an operating room system may receive parameters from the surgical computing system. For example, a lighting system within the operating room may receive parameters associated with modifying lighting in the operating room. An air handling system may receive parameters associated with modifying movement of air in the operating room. A display system may receive parameters associated with modifying the brightness of the display or the warmth of the color used on the display. The display system may be a surgical display and may comprise a monitor.

At 37132, the operating room may modify its operation consistent with the received parameters. For example, a lighting system may modify lighting intensity consistent with the received parameters. A lighting system may generate a light path to direct movement of a healthcare provider consistent with the parameters. An air handling system may modify the flow of air in the operating room constituent with the received parameters. A display system may modify the brightness of the display or modify the warmth of color used by the display.

A surgical computing system may be configured to monitor for particular surgical events, and to control one or more systems based upon detection that a surgical event has taken place. For example, the surgical computing system may be configured to monitor for particular, e.g., significant or critical, surgical events and, based on the detection of the event, may determine parameters for systems in order to prioritize particular data. The surgical computing system may be configured to monitor operating room noise levels and/or staff movements to identify one or more surgical events and, if the one or more surgical events are identified, determine parameters for controlling one or more systems. For example, the surgical computing system may determine parameters to control systems to control the display of monitored biomarkers and/or video. The parameters may control systems so that particular biomarkers are highlighted or are displayed in a prioritized manner.

Referring back to FIG. 26 , in connection with monitoring for occurrence of a surgical event, at 37118, the surgical computing system may be configured to obtain or receive monitored data associated with an operating room. The monitored data may comprise, for example, data associated with noise and/or movement in the operating room. The surgical computing system may receive and evaluate monitored data associated with staff activities and/or urgency of motion to identify patient critical events within the operating room. The surgical computing system may obtain and evaluate monitored data associated with surgeon biomarker data as described, for example, in U.S. patent application Ser. No. 17/156,300 filed Jan. 22, 2021, titled “Situation Adaptable Surgical Instrument Control” (attorney docket no. END9290USNP3), the contents of which are hereby incorporated herein by reference in their entirety. The surgical computing system may evaluate the monitored data associated with surgeon biomarker data and may determine based at least in part on the biomarker data that a particular task or event in a surgical procedure has been performed or is being performed.

At 37120, the surgical computing system may determine, based at least in part on the monitored data, one or more parameters for an operating room system such as, for example, a display system. The surgical computing system may determine, based at least in part on the monitored data, that a particular event in a surgical procedure has taken or is taking place in the operating room.

If the surgical computing system determines one or more surgical events has or is taking place, the surgical computing system may determine one or more parameters for one or more operating room systems. For example, the surgical computing system may determine one or more parameters associated with prioritizing display of data such as, for example, biomarker data on the display data. The biomarker data may be associated with, for example, the patient and/or one or more of the healthcare professionals in the operating room.

At 37122, the surgical computing system may communicate the one or more parameters to operating room systems which may include, for example, one or more display systems. At 37128, the parameters may be received at the operating room systems and at 37132 the parameters may be used to modify operation of the systems. For example, the parameters may be used by a display system to modify aspects of a display. Biomarker data associated with the patient may be prioritized on the display system.

The surgical computing system may analyze monitored data associated with staff activities and/or urgency of motion to identify patient critical surgical events and may initiate an identification of monitored biomarkers, surgical video events, etc., that may be a cause of the critical up tick of activity. The surgical computing system may utilize the identification of a particular step in a surgical procedure and/or identification of an issue relative to a patient. The surgical computing system may determine system parameters to prioritize display of associated biomarkers and/or video. The parameters may instruct a display system to include increased focus on a particular surgical site location. The parameters may instruct a display system to increase focus and/or center a camera on the surgical site issue. The parameters may configure one or more systems to display related biomarkers. The parameters may instruct a display system to have their particular video feeds prioritized on a display system. The parameters may instruct a display system to increase a screen size and/or other visibility aspects.

A surgical computing system may be configured to monitor operating room data and may determine, based upon the monitored data, parameters for controlling lighting systems in the operating room. The surgical computing system may receive monitored data associated with one or more healthcare professionals in the operating room. The monitored data may comprise data associated with the focus of a healthcare professional, the location of the healthcare professional, and/or the activity of the healthcare professional. The monitored data may further comprise data relating to the surgical task that is being undertaken. The surgical computing system may determine, based on the monitored data, parameters for controlling or adjusting lighting systems in the operating room. The surgical computing system may generate and communicate parameters to improve operating room lighting and visualization based on the monitored data associated with the healthcare professionals and the surgical tasks being undertaken.

Referring to FIG. 26 , at 37118, the surgical computing system may obtain or receive monitored data associated with an operating room. The monitored data may comprise data associated with a healthcare professional in the operating room. The data associated with the healthcare professional may comprise data relating, for example, to the activity, positioning, and/or bio-measurements associated with the healthcare professional. The data associated with the healthcare professional may comprise, for example, data associated with one or more of visual focus, a task being performed, or position associated with the healthcare professional.

At 37120, the surgical computing system may determine, based at least in part on the monitored data, one or more parameters for one or more lighting systems associated with the operating room. If the monitored data comprises data associated with a visual focus of the healthcare professional, the surgical computing system may determine based at least on the data associated with the visual focus, one or more parameters for one or more lighting systems to adjust lighting consistent with the visual focus of the healthcare professional. If the monitored data comprises data associated with a task being performed by the healthcare professional, the surgical computing system may determine based at least on the data associated with the task being performed, one or more parameters for one or more lighting systems to adjust lighting consistent with the task being performed. If the monitored data comprises data associated with location of the healthcare professional, the surgical computing system may determine based at least on the data associated with location of the healthcare professional, one or more parameters for one or more lighting systems to adjust lighting consistent with the location of the healthcare professional. The parameters generated by the surgical computing system may be parameters for one or more lighting systems including, for example, overhead lights, Bovie lights, lights associated with an instrument tray, floor lights, laser lights, and ambient lights.

At 37122, the surgical computing system may communicate the one or more parameters to systems associated with the OR. The surgical computing system may communication one or more parameters, for example, to one or more lighting systems associated with the operating room.

At 37128, one or more systems associated with the operating room may receive the parameters. At 37132, the one or more systems may modify their operations based upon the received parameters. For example, one or more lighting control systems may modify operation consistent with the received parameters. For example, one or more lighting control systems may modify operation to focus light consistent with the visual focus of the healthcare professional, the task being performed, and/or the location of the healthcare professional.

Monitoring systems located in the operating room may track the motions of healthcare professionals including tracking eye motions and locations to determine the focus of attention of a healthcare professional. The surgical computing system may receive monitored data associated with the motions and visual focus and determine parameters to adjust ambient and focal light sources that may enable the healthcare professional to see more easily. The parameters may be directed at modifying the visual display of display monitors to improve visualization. The parameters may modify the white balance and/or contrast of a display monitor. The parameters may be directed to lighting systems within the operating room to improve visualization of the surgical site including the display monitors being used. The parameters may instruct lighting systems to reduce potential glare and/or to lower lighting to improve monitor color and contrast.

The surgical computing system may generate parameters for controlling lighting systems to minimize collisions and tripping hazards. During laparoscopic surgery, the operating room lights may be turned off or minimized, which may result in healthcare professionals other than those performing the surgery working in relative darkness. The lack of lighting may increase the risk of a collision, tripping, and/or selecting the incorrect instrument. The surgical computing system may receive monitored data indicating the status of a surgical procedure and data associated with motion of healthcare professionals in the operating room. The surgical computing system may determine, based on the monitored data, to generate parameters instructing a lighting system to indicate with lighting a path having reduced risk of collision. The parameters may instruct an LED lighting system to illuminate a path for the healthcare professional.

The surgical computing system may generate parameters for controlling lighting systems to facilitate instrument exchange and handling of instruments relative to a Mayo stand. During surgery, an incorrect instrument for a task may inadvertently be retrieved due to poor lighting. Performing surgery in inadequately lighted areas may cause delays or distract focus. The monitoring system may identify and communicate monitored data associated with instruments that are in use as well as the current step in a surgical procedure. The surgical computing system may determine, based on the received monitored data, parameters for an operating room lighting system to provide visual cues to a healthcare professional. The parameters may instruct an LED lighting system to generate light to suggest to the healthcare professional one or more surgical instruments that may be appropriate for a next step. A spotlight, an LED indicator, or some other visual cue may be focused on the appropriate instrument. The surgical computing system may also generate parameters to control one or more lighting systems to indicate a return location for a surgical instrument. The parameters may cause a lighting system to generate an LED indication or spotlight to where an instrument may be placed. The indicated location may be one that is relatively safe to avoid falling to the floor and/or one that is ergonomically efficient for the healthcare professional.

The surgical computing system may generate parameters that control lighting systems in the operating room so as to minimize distraction and saturation of screens and visual imaging.

Human cortisol levels may drop significantly under artificial or poor lighting conditions. Humans may be stressed and have less ability to stabilize energy levels. Exposure to dim light as well as too much artificial light may cause a person to become sleepy and/or to become stressed. The surgical computing system may receive monitored data associated with visual cues of healthcare professionals and may generate parameters for controlling the lighting systems in a manner to increase focus. The parameters may adjust the intensity and/or color temperature of the light to enhance alertness of the healthcare professionals.

FIG. 27 depicts example timing charts illustrating example adaptive control of lighting systems based on monitored aspects of the operating room during a surgical procedure. The surgical computing system may receive monitored data associated with the operating room and may generate parameters for controlling lighting systems based on the received monitored data. Referring to FIG. 27 , at section A, example adaptive control of lighting systems in response to robotic control activities is depicted. In a top graph portion of section A, use of robotic surgical controls over time is depicted, with time extending from left to right. In the bottom graph portion of section A, operation of lighting systems, which may be measured in lumens, across time and in response to parameters received from the surgical computing system is depicted. As shown in the top graph portion of section A, initially the robotic controls are not in use. During this period of non-use, the overhead lighting system may receive parameters from the surgical computing system that may cause a ceiling lighting system to generate white light. The surgical computing system may receive monitored data indicating a surgical procedure may soon take place. For example, the surgical computing system may receive data indicating movements of healthcare professionals and/or instruments consistent with commencing a surgical procedure. The surgical computing system may generate and communicate parameters to illuminate surgical lighting, which may be referred to as Bovie lighting. In response, and as indicated in the lower graph portion of section A, the surgical lighting or Bovie lighting may commence at time t1 (indicated on the upper graph portion of section A).

As shown in the upper graph in section A, at time t2, the healthcare professional, e.g., surgeon, may transition into a console for controlling a surgical robot. The surgical computing system may receive monitored data indicating the healthcare professional has transitioned into the console. In response, the surgical computing system may generate parameters to control lighting systems in the operating room. For example, the surgical computing system may generate parameters to transition overhead lighting from white ceiling lighting to blue ceiling lighting and to reduce the intensity of the lighting. As shown, at time t3 (indicated on the upper graph portion of section A), the overhead lighting system may reduce intensity, e.g., lumens, and change color to blue. At time t4 (indicated on the upper graph portion of section A), the healthcare professional may begin transitioning out of the robot control console. In response to receiving monitored data indicating a transition out of robot control, the surgical computing system may generate and communicate parameters to the overhead lighting system to increase intensity as illustrated in the lower graph portion of the section A. The surgical computing system may communicate parameters to the Bovie lighting system to increase intensity upon the transition of the healthcare professional out of the robot at time t5 (indicated in the upper graph portion of section A). At time t6 (indicated in the upper graph portion of section A), when the healthcare professional begins to again transition into the robot console, the surgical computing system may generate parameters to modify the overhead and Bovie lighting in a similar manner as previously described.

The surgical computing system may receive monitored data indicating the healthcare professional has again transitioned out of the robot and may have begun other surgical steps. In response to the received monitored data indicating the robotic surgical steps are finished, the surgical computing system may generate and communicate parameters to modify operation of lighting systems in the operating room. The surgical computing system may generate parameters to cause a ceiling lighting system to generate white light as indicated at time t7.

Referring to FIG. 27 , at section B, example adaptive control of lighting systems in response to handling of surgical devices in the operating room is depicted. In a top graph portion of section B, hand off of surgical instruments is represented by impulses. As shown, numerous instrument handoffs are performed across time depicted left to right. In the bottom graph portion of section B, operation of lighting systems, which may be measured in lumens, across time and in response to parameters received from the surgical computing system is depicted. In the example of section B, operation of lighting systems associated with an instrument tray is depicted.

As shown in the upper portion of section B, during the period before time t2 (shown in the upper graph of section A) which corresponds to a period before the surgeon enters the robotic surgical control, several handoffs of surgical instruments which may be trocars and/or scopes may take place. During this period before time t2, as noted in section A, white ceiling lighting may be in use in the operating room. Lighting systems associated with the instrument tray may not be needed during the time that white ceiling lighting is employed. At time t3, when as indicated in section A, the healthcare professional begins using the robotic surgery system and the overhead lighting is reduced and takes on a blue tint, the surgical computing device may communicate parameters to lighting systems associated with illuminating an instrument tray as indicated beginning at time t3 in the lower portion of section B. During the period between time t3 and t4, representing the initial period that the surgeon is using the robotic surgical device, the instrument tray is illuminated. When an instrument handoff takes place during this period as indicated by an impulse in the upper portion of section B, the surgical computing system communicates parameters to increase the instrument tray lighting as noted by an impulse in lumens in order to provide additional light during the handling of the surgical instrument. During the period between time t4 and time t5 when the healthcare professional is not using the robot control and the overhead blue lighting is elevated (as noted in the bottom portion of section A), the instrument tray may not be illuminated even in the instance a surgical device handover is made. Beginning at time t6 when the healthcare professional again operates the robotic surgical device, the surgical computing system communicates parameters for the lighting systems to illuminate the surgical tray. When instrument handoffs take place during this period as indicated by impulses in the upper graph in section B, the surgical computing system communicates parameters to the lighting system to increase the intensity of lighting provided to the instrument tray as indicated by the impulses in lumens in the lower graph depicted in section B. After time t7, corresponding to the end of reduced blue ceiling lighting and the reengaging of the white ceiling lighting as depicted in the bottom graph of section A, the lighting systems may cease applying light to the instrument tray.

Referring to FIG. 27 , at section C, example adaptive control of lighting systems in response to healthcare professional traffic in the operating room is depicted. In a top graph portion of section C, periods of movement within the operating room associated with healthcare providers are represented by impulses. As shown, numerous movements by healthcare providers occur across time. For example, movements within the operating room may correspond to traffic into and out of the operating room, movement of a surgeon into and out of the position to use the robotic surgical instrument, handing off of surgical instruments, etc. The bottom graph of section C depicts activation of floor lighting systems. The floor lighting systems may comprise, for example, laser or LED lights that direct persons and movements in the operating room, and lights associated with equipment in the operating room such as the surgical table that provide lighting of the floor in the area of the equipment. As shown in section C, when healthcare provider movements and traffic occur, as indicated by impulses shown in the top graph of section C, floor lighting systems are activated as indicated by the corresponding impulses in the bottom graph of section C. The surgical computing system may receive monitored data associated with the movements of the healthcare professionals and may generate and communicate parameters to the floor lighting systems. During the period that blue ceiling lighting is activated during control of the robotic surgical system as indicated in section A, lighting such as, for example, underbed lighting may be activated as noted in the lower graph of section C. The amplitude of the floor lighting may vary at different points in time to adjust for ambient light.

Referring to FIG. 27 , at section D, example adaptive control of display monitor features in response to or based on ambient light is depicted. In the top graph of section D, ambient light levels measured near a display monitor are graphed over time. As shown, measured ambient light may vary over time and may reflect activities in the operating room such as, for example, doors opening and closing, adjustments to ceiling lighting systems, implementation of blue lighting during use of robotic surgery, etc. As illustrated, the ambient light at the monitor may be relatively higher when ceiling lighting systems generate white lighting and the ambient light at the monitor may be relatively lower when the blue ceiling lighting may be employed during robotic surgery.

The middle graph of section D depicts the brightness, which may be measured in lumens, that is applied to the display monitor over time. The surgical computing system may control the display monitor brightness in response to the ambient light in the operating room. As illustrated, as the ambient light increases, the brightness of the monitor may be adjusted upward to maintain visibility during periods of increase ambient light. During periods of relatively low ambient light such as may correspond to periods of robotic surgery, the brightness of the monitor may be adjusted downward. The monitor brightness may follow the ambient light in a manner to maintain preferred contrast at the display monitor.

The bottom graph of section D depicts the color that may be employed at the display monitor over time. Values above zero may be referred to as warm colors, while values below zero may be referred to as cool colors. As illustrated, during periods of relatively high ambient light and corresponding relatively high monitor brightness, the monitor display color may be adjusted to a relatively cool temperature. During periods of relatively lower ambient light and correspondingly relatively lower monitor brightness, the monitor display color may be adjusted to a relatively warm temperature. As illustrated, during the period that robotic surgery may be taking place, corresponding to a period of relatively low ambient light, the surgical computing system may communicate parameters to the display monitor to adjust to using warmer colors for display.

A surgical computing system may be configured to monitor operating room data and may determine, based upon the monitored data, to instruct air handling control systems associated with the operating room to modify air flow and/or filtration in the operating room. The surgical computing system may receive monitored data that may be associated with, for example, air quality and/or air particulates in the air in the operating room. The surgical computing system may determine, based on the monitored data, parameters for controlling or adjusting operation of air handling and filtration systems. The parameters may adjust operating room systems that perform surgical insulation, smoke evacuation, and/or air filtration.

Referring to FIG. 26 , at 37118, the surgical computing system may obtain or receive monitored data associated with an operating room. The monitored data may comprise data associated with air composition in the operating room. The data associated with air composition in the operating room may comprise data associated with particulates in the air.

At 37120, the surgical computing system may determine, based at least in part on the monitored data, one or more parameters for one or air handling systems in the operating room. The one or more air handling systems may comprise, for example, one or more of an air filtration system, a smoke evaluation system, an air handler system, or an air pressure system. If the monitored data comprises data associated with particulates in the air in the operating room, the surgical computing system may determine one or more parameters for one or more air duct controls to adjust air flow in the operating room. The surgical computing system may determine one or more parameters for one or more air pressure controls to adjust air flow in the operating room. The surgical computing system may determine one or more parameters for one or more some evacuation controls to adjust smoke in the operating room.

At 37122, the surgical computing system may communicate the one or more parameters to systems associated with the operating room. The surgical computing system may communicate one or more parameters, for example, to one or more air handling systems associated with the operating room.

At 37128, one or more systems associated with the operating room may receive the parameters. At 37132, the one or more systems may modify their operations based upon the received parameters. For example, one or more air handling systems may increase intensity of operation to evacuate air from a particular portion of the operating room, to increase the volume of air being processed by an air filtration system, and/or to increase pressure of air flow in particular portion of the operating room in response to the received parameters.

The operating room environment has been thought to contribute to surgical site infection rates. The quality of operating room air, disruption of airflow, and other factors may increase contamination risks. Air particulate counts (APCs) may be impacted by increases in foot traffic, opening of doors to the operating room, movement of equipment as well as other activities that may take place in the operating room. These activities have the potential of elevating bacteria spread. A surgical computing system may receive monitored data associated with air particles as well as video or RFID tags and may identify a location of activity in the operating room. The surgical computing system may determine parameters for controlling duct and/or air control valves to alter the flow of air and direct the flow of clean air toward the area of movement. The surgical computing system may monitor video data to identify a piece of equipment is about to be moved and may respond with parameters to impact the flow of air. For example, if a monitor or surgical display is to be moved, the surgical computing system may communicate parameters that cause air handling systems to direct air flow from the direction of the surgeon and/or other staff towards the monitor or surgical display in order to direct air away from the surgical site until monitored data of the air particulates are acceptable. The surgical monitoring system may receive data associated with video and RFID tags and may determine based on the data a staff member is either entering or leaving the operating room. The surgical monitoring system may determine and communicate parameters that cause air handling systems to alter the direction of air flow and/or the velocity of air flow from the direction of the surgeon and/or staff towards the door. The additional flow may direct particulates from the surgical site and may continue until the air particulate monitoring indicates the readings are acceptable.

An operating room environment may have one or more air handling systems that are adapted to generate positive and negative pressure in the operating room to control air flow, control air pressure, and filter air. To counter potential bacteria spread associated with increased traffic, door openings and/or equipment movement, the surgical computing system may determine parameters for controlling an air handling system to create negative air pressure to pull air away from the surgical site until the air particulate monitoring indicates the readings are acceptable.

Surgical smoke evacuation systems may be high-flow vacuum sources that may be used to capture at the surgical site smoke aerosols and gasses that may have been generated during the use of lasers and electrosurgical units. The American Occupational Safety and Health Administration has estimated that 500,000 workers may be exposed to laser and electrosurgical smoke each year. The use of surgical masks alone may not provide adequate protection from surgical smoke. A surgical computing system may receive monitored data associated with particulates in the operating room air and video data may identify when smoke evacuation may be needed. The surgical computing system may determine based upon the monitored data to generate and communicate parameters to one or more smoke evacuation systems to lessen the amount of smoke in the surgical area. The parameters may control a level of operation of a vacuum pump which removes smoke from the surgical area.

A surgical computing system may be configured to monitor operating room data and may determine, based upon the monitored data, to instruct heating and/or cooling control systems associated with the operating room to either lower or increase room temperature. The surgical computing system may receive monitored data that may be associated with, for example, patient and/or healthcare professional's biomarkers. The surgical computing system may determine, based on the monitored data, parameters for controlling the heating and/or cooling systems associated with the operating room. The heating and/or cooling systems may be ambient and/or local control systems. The room temperature control may be based on patient or healthcare professional biomarker tracking.

Referring to FIG. 26 , at 37118, the surgical computing system may obtain or receive monitored data associated with the operating room. The monitored data may comprise biomarker data associated with one or more of a patient and/or a healthcare professional located in the operating room. The biomarker data may comprise, for example, data associated with a body temperature associated with one or more of the patient or the healthcare professional.

At 37120, the surgical computing system may determine, based at least in part on the monitored data, one or more parameters for one or more temperature control systems in the operating room. If the monitored data associated with body temperature associated with one or more of the patient or the healthcare professional is determined by the surgical computing system to be below a threshold, the surgical computing system may determine one or more parameters associated with the one or more temperature control systems increasing air temperature. If the monitored data associated with body temperature associated with one or more of the patient or the healthcare professional is determined by the surgical computing system to be above a threshold, the surgical computing system may determine one or more parameters associated with the one or more temperature control systems decreasing air temperature.

At 37122, the surgical computing system may communicate the one or more parameters to systems associated with the operating room. The surgical computing system may communication one or more parameters, for example, to one or more temperature control systems associated with the operating room.

At 37128, one or more systems associated with the operating room may receive the parameters. At 37132, the one or more systems may modify their operations based upon the received parameters. For example, one or more temperature control systems may modify operation to either increase or decrease air temperature consistent with the received parameters.

The surgical computing system may receive biomarker data associated with a patient and/or healthcare provider in the operating room. The surgical computing system may generate parameters for controlling temperature control systems based on monitored data associated with biomarker data for the patient and/or healthcare provider. The surgical computing system may further evaluate criticality of biomarker level, procedure type, and/or procedure step in determining parameters for controlling temperature. The surgical computing system may determine to override what may be considered comfortable or normal room temperature settings as a means for controlling biofunctions critical to surgical procedures. For example, for heart surgery or other circulatory procedures, it may be beneficial to lower the patient heart rate or pain sensitivity by lowering the room temperature to lower than normal in order to slow physiologic functions. In order to offset the hypothermic effects of large volume CO2 insulation usage on room temperature, the surgical computing system may generate parameters to control temperature control systems to create an equilibrium of patient temperature regardless of gas introduction and expulsion.

The surgical computing system may determine and communicate parameters based on the body temperature of healthcare professionals and/or the patient. The surgical computing system may receive data associated with body temperature, e.g., core body temperature, of healthcare professionals and/or the patient. Studies show that high/low temperatures may affect the ability to learn and or function. When temperatures are too hot or too cold, the brain may constantly remind the body to do something about the condition. Due to the constant interruption, it is difficult to stay focused. In addition to being uncomfortable, an individual may be distracted. If a person feels cold, they may use a substantial amount of energy attempting to keep warm. This leaves less energy for concentration, inspiration, and focus. Core body temperature may rise due to physical exertion or stress, both of which may impact performance. Thermal imaging systems and thermometers may be used to gather temperature data for healthcare professionals which may be communicated to the surgical computing system. The surgical computing system may receive the data and may determine parameters for adjusting the volume and/or temperature of the room air and possibly directing air at a particular individual to maintain optimal body temperature.

Human performance may be negatively affected when core body temperatures are not between 36.5 and 37.5 degrees Celsius. A surgeon that has elevated body temperatures may begin sweating which may distract his focus. It may also lead to time delays as sweating may necessitate stopping to wipe away sweat. Sweat may contaminate the site. A sweating surgeon may be more likely to contaminate a surgical field than the non-sweating surgeon. Monitoring physical signs and core temperature and employing monitored data to generate parameters for controlling the environment may mitigate sweating by the surgeon and/or other professionals.

Cold or hot core temperature may lead to shivers or tremors in healthcare professionals. Shaky hands or tremors may impact grasping of instruments which may lead to less control with the surgical site and increased distractions.

The surgical computing system may determine parameters for controlling temperature control systems based on monitored data associated with patient temperature. During and post-surgery, the patient's body temperature may drop, sometimes as much as 6 degrees Fahrenheit. The patient may be only partly covered, may receive cold intravenous fluids, and cold air may be pumped into the patient's lungs. Anesthetics received by a patient may upset the body's ability to regulate its internal body temperature. These factors may increase the metabolic rate and strain the patient's heart. It may also result in pulling apart of incisions, damage delicate surgical repairs, and even result in broken teeth. Accordingly, the surgical computing system may generate, based on monitored data associated with a patient, parameters for controlling temperature proximate the patient.

A surgical computing system may be configured to monitor operating room data and may determine, based upon the monitored data, to implement room conditions associated with a particular healthcare provider who may be participating in an ongoing surgical procedure. The surgical computing system may determine the monitored data indicate or are associated with a particular step, e.g., critical step, of a surgical procedure. If the surgical computing system determines the monitored data indicate a particular step in a surgical procedure is being performed, the surgical computing system may determine parameters for operating room systems associated with preferred room conditions. The surgical computing system may be configured to determine parameters that implement hierarchical priority based adjustments to equipment based on situational awareness and importance of a step in a surgical procedure.

Referring to FIG. 26 , at 37118, the surgical computing system may receive monitored data associated with the operating room. The monitored data may comprise data associated with a step in a surgical procedure being performed in the operating room.

The surgical computing system may be configured to determine parameters associated with a healthcare professional who is participating in the surgical procedure being performed in the operating room. At 37120, the surgical computing system may determine, based at least in part on the monitored data and operational parameters associated with a healthcare professional participating the surgical procedure, one or more parameters for one or more systems in the operating room. The parameters associated with the healthcare professional may comprise parameters associated with preferences for the operating room. The received monitored data may be associated with a step in the surgical procedure. The surgical computing system may determine, based on the parameters associated with preferences for the operating room and the data associated with the step in the surgical procedure, one or more parameters associated with adjustments to the systems in the operating room. The one or more parameters associated with adjustments to the systems in the operating room may comprise parameters associated with increasing volume of speech associated with the healthcare professional. The one or more parameters associated with adjustments to the systems in the operating room may comprise parameters associated with increasing noise cancellation in the operating room. The one or more parameters associated with adjustments to the systems in the operating room may comprise parameters associated with augmenting audible cues associated with the surgical procedure.

At 37122, the surgical computing system may communicate the one or more parameters to systems associated with the operating room. The surgical computing system may communicate the one or more parameters, for example, to one or more audio/visual system associated with the operating room.

At 37128, one or more systems associated with the OR may receive the parameters. At 37132, the one or more systems may modify their operations based upon the received parameters. For example, one or more audio/visual systems may modify operation to increase or decrease volume of speech reproduction, increase or decrease noise cancellation, and/or augment audible cues.

The surgical computing system may determine, based on the received monitored data, parameters for operating mom systems and associated with augmenting or increasing speech or volume for particular healthcare providers in the operating room. The surgical computing system may determine, based on the received monitored data, parameters for operating room systems and associated with adjustable segmented active noise cancellation. The surgical computing system, in determining the parameters, may balance noise cancellation with interactive activity associated with a surgical procedure. The surgical computing system may generate parameters associated with quadrant noise cancellation which may apply for an audio system with speakers that are split within four quadrants of a room. The surgical computing system may determine parameters that causes the audio system to direct anti-noise in a particular quadrant and direct audio into a separate quadrant. The surgical computing system may generate parameters for an operating room audio system comprising speakers that follow a healthcare professional in the operating room. The surgical computing system may determine parameters for such an audio system whereby the parameters control the speakers to direct audio to particular healthcare professionals. Directing audio to particular individuals assists healthcare professionals in maintaining focus on a task or job while avoiding distractions or interruptions.

The surgical computing system may determine, based on the received monitored data, parameters that result in restricting operating room entry or movement within the operating room. For example, the surgical computing system may determine parameters for systems that open and control doors to the operating room.

The surgical computing system may determine, based on the received monitored data, parameters that result in quieting extraneous sounds. For example, the surgical computing system may determine parameters to reduce volume on audio systems and silence phone calls.

An operating room may make use of augmented reality systems such as, for example, systems and implementations described in U.S. patent application Ser. No. 17/156,329 filed on Jan. 22, 2021 and titled “Audio Augmented Reality Cues to Focus on Audible Information” (attorney docket no. END9290USNP18), the contents of which are hereby incorporated herein by reference in their entirety. The surgical computing system may be configured to determine parameters for an augmented reality system to control and moderate audible reality cues to center focus on key audible feedback.

The surgical computing system may be configured to determine parameters for control of operating room systems based on awareness of the step being performed in a surgical procedure, situational awareness of the task, and the surrounding monitored environmental cues, where the parameters are selected to adjust operation of systems to be consistent with a healthcare professional's preferences. For example, as the surgical computing system determines the monitored data indicates particular surgical tasks are being performed and indicate an ambient audible level is above a threshold, the surgical computing system may determine parameters to adjust systems within the operating room lower the noise level based on a prioritized or criticality list of the equipment and their associated contributions to the elevated levels.

A surgical computing system may be configured to monitor OR data and, based upon the monitored data, may determine to generate parameters associated with the environmental control devices. The surgical computing system may determine to generate parameters associated with adjusting, for example, one or more of the intensity, duration, and/or rapidity of operation of environmental control devices. For example, the surgical computing system may determine to generate parameters associated with the intensity that an air flow control system may operate. The surgical computing system may apply thresholds to considering the monitored data and may adjust the thresholds that the surgical computing system may apply over time based on the importance of the measure to the patient or a healthcare professional.

Referring to FIG. 26 , at 37118, the surgical computing system may obtain or receive monitored data associated with an operating room. The monitored data may be associated, for example, with air-born particles in the OR. The monitored data may comprise data associated with an occurrence of exhaling by an infectious patient. The monitored data may comprise data associated with an occurrence of an exhaust or smoke plume associated with a cancerous patient.

At 37120, the surgical computing system may determine, based on the monitored data, a risk level to a healthcare professional in the OR. The surgical computing system may determine based on monitored data associated with air-born particles in the OR that the risk level is an elevated risk level. The surgical computing system may determine, based on one or more determine risk levels, one or more parameters for operating one or more systems in the OR. If the surgical computing system determines that the monitored data indicates an elevated risk, the surgical computing system may determine one or more parameters for an air filtration system associated with the OR. The parameters may be associated with increasing the intensity of operation of the air filtration system.

At 37122, the surgical computing system may communicate the one or more parameters to systems associated with the OR. The surgical computing system may communication one or more parameters, for example, to one or more air handling systems associated with the OR.

At 37128, one or more systems associated with the OR may receive the parameters. At 37132, the one or more systems may modify their operations based upon the received parameters. For example, one or more air handling systems may increase intensity of operation to evacuate air from a particular portion of the OR in response to the received parameters.

A surgeon performing a surgical procedure may use an advanced energy device on near cancerous tissue which may create a relatively large smoke plume. Monitoring data associated with the air plume may be received at the surgical computing system which may determine, based on the received data associated with the plume, to modify the rate of smoke or air evacuation, increase the efficiency of the filtration system, and/or increase room filtration. The surgical computing system may communicate parameters associated with the modified operations to the corresponding air and filtration systems in the OR.

An anesthesiologist or bronchologist may introduce a ventilation tube to a patient who is known to be infectious. The patient may sneeze or otherwise exhale. Monitoring data associated with the sneezing and/or the placement of the ventilation tube may be received at the surgical computing system. The surgical computing system may detect a cough or sneeze by the patient based on monitored biomarkers of the patient and/or may receive data indicating a level of danger associated with infective droplets. The surgical computing system may determine, based on the detected cough or sneeze as indicated by the monitored data, to increase the speed and/or capacity of one or more filtration and/or extractions systems. The surgical computing system may determine to rapidly increase the intake and filtration due to a detected particle count and anticipating the increase in particles in route and the potential impact of failure to catch the particles. The surgical computing system may determine parameters associated with modifying the operation of the air handling systems and communicate those parameters to the systems.

Accordingly, systems, methods, and instrumentalities are disclosed for adaptive control of operating room systems based upon monitored data associated with the operating room. Monitoring systems within the operating room may be configured to collect data regarding, for example, the patient being treated in the operating room, the healthcare professionals participating in the surgical procedure, and the environment in the operating room. The monitored data may be communicated to a surgical computing system. The surgical computing system may receive the monitored data and may determine, based upon the monitored data, parameters for controlling various systems associated with the operating room. The surgical computing system may evaluate received monitored data in view of the surgical tasks that are ongoing in the operating room. The surgical computing system may communicate the parameters to the operating room systems. The parameters may be received, for example, at lighting (e.g., ambient and focus) systems, air filtration and extraction systems, smoke evacuation systems, sound systems, video systems, and/or display monitor systems. The systems may modify their operation based upon the received parameters.

The computing system may monitor healthcare professionals (HCPs) in an operating room (OR) and provide parameters associated with improving performance for surgical procedure(s) and/or maintenance of operating room(s). The parameters associated with improving performance for surgical procedure(s) and/or maintenance of operating room(s) may be included in recommendations, adjustments, and/or feedback. The parameters may be associated with movement of HCPs, activities of surgical staff members, equipment location and/or usage, and/or the like.

For example, the computing system may monitor HCP motion, interactions, and movement within the OR and generate parameters and/or recommendations to improve the performance of surgical procedures and/or maintenance of ORs. The motions, interactions, and movement of the HCPs monitored throughout surgical procedure(s) may be analyzed. Improvements for OR layout, surgical instrument mix, and/or surgical site access may be identified, for example, to improve efficiency of motion and/or performance of the surgical procedure.

The computing system may obtain and analyze surgical monitoring data associated with a surgical procedure. The surgical monitoring data may include the activities of HCPs, equipment location, equipment usage, downtime and/or wait times, and/or the like associated with a surgical procedure. The computing system may, based on the analysis, for example, generate one or more adjustment parameters. The adjustment parameters may improve performance associated with a surgical procedure, for example, such as unnecessary staffing members of HCPs for the surgical procedure. The adjustment parameters may include one or more of surgical instrument mix selection, surgical site access location, OR layout, HCP staffing for a surgical procedure and/or procedural step, surgical equipment placement, surgical instrument usage, HCP positioning, surgical instrument preparation, audio and/or display outputs, and/or the like.

For example, the computing system may receive monitored data associated with an OR and/or surgical procedure. The monitored data may include data associated with one or more of OR layout, HCP positioning, HCP movement, surgical equipment location, surgical instrument mix, surgical site access locations, HCP staffing, trocar placement, HCP activities, HCP behavior and/or emotions, and/or the like.

The computing system may obtain a surgical procedure plan. The procedure plan may include steps for a surgical procedure, staffing, OR layout, surgical instrument mix, and/or the like. The computing system may determine procedure data associated with a surgical procedure (e.g., ongoing surgical procedure, an upcoming surgical procedure, and/or a past procedure). The surgical computing system may determine procedure data using a situationally aware surgical system. The surgical computing system may include a situationally aware surgical system 5100 as described herein with respect to FIG. 11 . The surgical computing system may derive or infer information related to the surgical procedure, for example, based on the monitored data. The procedure data may include data associated with consistency of HCP actions relative to the procedure plan, for example, such as whether steps of a procedure plan have been performed and/or have been performed timely. For example, the surgical computing system may determine the current procedural step in a surgical procedure based on monitored data.

The surgical computing system may determine one or more adjustment parameters associated with improving performance of a surgical procedure and/or maintenance of the OR, for example, based on the monitored data, procedure plan, and/or procedure data. The adjustment parameter(s) may include adjustments to one or more of OR layout, HCP positioning, HCP movement, surgical equipment positioning, surgical instrument positioning, surgical site access positioning, HCP activities, HCP staffing, surgical instrument usage, and/or the like. The surgical computing system may send an indication of the adjustment parameter(s). The computing system may communicate the adjustment parameter(s) to one or more systems associated with the OR. For example, the computing system may communicate the adjustment parameter(s) to a system configured to control communication system(s) in the OR. The communication system may include a surgical display or speaker system. For example, the surgical display may present the adjustment parameter(s).

The computing system (e.g., a surgical computing system) may include a surgical hub 20002 as described herein with respect to FIG. 2 . For example, the surgical computing system may include at least one of the following: a surgical hub 20006 in communication with a cloud computing system 20008, for example, as described in FIG. 2 . The surgical computing system may include at least one of the following: a surgical hub 20006 or a computing device 20016 in communication with a could computing system 20008. The cloud computing system 20008 may include at least one remote cloud server 20009 and at least one remote cloud storage unit 20010. The computing system may be or may include an HCP monitoring system such as the HCP monitoring system 20000, 20002, 20003, or 20004 as described herein with respect to FIGS. 1-3 . The computing system may be a computing system operatively connected to the HCP monitoring system(s) 20000, 20002, 20003, and/or 20004. The computing system may be or may include the computing system 20271 described herein with respect to FIG. 9 . The computing system may be or may include the computer system 20063 described herein, for example, with respect to FIG. 4 .

The surgical monitoring data may be obtained via the surgical hubs. For example, a surgical hub may obtain surgical monitoring data from various sensing systems such as the wearable sensing system(s) 20011, and/or environmental sensing system(s) 20015 described herein with respect to FIG. 1 . The surgical hub may obtain monitored data from HCP monitoring devices 35510, environmental monitoring devices 35512, patient monitoring devices 5124, and/or modular devices 5102 as described herein with respect to FIG. 11 .

FIG. 28 illustrates an example analysis associated with surgical procedures. Surgical procedures may be plotted on a graph 37600 based on outcome success and efficiency. Data collected and analyzed from previous procedures 37602 may be plotted based on outcome success and efficiency. For example, the computing system may determine outcome success and efficiency of the surgical procedures based on monitored data, surgical procedure plan, and/or surgical procedure data. Outcome success may be determined based on whether a surgical procedure was successful, whether surgical complications occurred, and/or the like. Efficiency may be determined based on duration of the surgical procedure, number of HCPs present for the surgical procedure, number of instruments used for a surgical procedure, and/or the like.

As shown in FIG. 28 , a surgical procedure may be plotted based on the outcome success and efficiency. The surgical computing system may determine adjustment parameters that may improve efficiency for a surgical procedure, for example, such as an improved OR layout and/or instrument mix. As shown at 37604, the surgical computing system may indicate on graph 37600 the improved efficiency associated with the determined adjustment parameters.

The surgical computing system may determine adjustment parameters that may improve efficiency for surgical procedure 37604, for example, such as improved movement of people and/or instruments. As shown at 37606, the surgical computing system may indicate on graph 37600 the improved efficiency (e.g., over surgical procedure 37604) associated with the determined adjustment parameters.

The surgical computing system may determine adjustment parameters that may improve outcome success for surgical procedure 37606, for example, such as reduction in door and/or air movements and traffic. As shown at 37608, the surgical computing system may indicate on graph 37600 the improved outcome success (e.g., over surgical procedure 37606) associated with the determined adjustment parameters.

The surgical computing system may determine adjustment parameters that may improve efficiency for surgical procedure 37608, for example, such as improved trocar tracking, angle, location, exchanges, and the like. As shown at 37610, the surgical computing system may indicate on graph 37600 the improved efficiency (e.g., over surgical procedure 37608) associated with the determined adjustment parameters.

The surgical computing system may determine adjustment parameters that may improve outcome success for surgical procedure 37610, for example, such as indications or notifications to avoid missed procedural steps based on tracking the OR. As shown at 37612, the surgical computing system may indicate on graph 37600 the improved outcome success (e.g., over surgical procedure 37610) associated with the determined adjustment parameters.

The surgical computing system may determine adjustment parameters that may improve efficiency for surgical procedure 37612, for example, such as improved instrument mix and/or instrument utilization based on monitoring data. As shown at 37614, the surgical computing system may indicate on graph 37600 the improved outcome success (e.g., over surgical procedure 37612) associated with the determined adjustment parameters.

In an example, the surgical computing system may receive monitored data associated with the current surgical procedure. Based on the monitored data, the surgical computing system may determine adjustment parameters for the current surgical procedure, for example, that may improve the efficiency and/or outcome success. For example, the surgical computing system may determine adjustment parameters, which may include one or more of modifying an OR layout, modifying an instrument mix, reducing movement of people, reducing movement of surgical instruments, reducing door/air movements and traffic, modifying trocar tracking, angle, location, and exchanges, notifying staff to avoid missed procedural steps, adjusting surgical instrument mix, adjusting surgical instrument utilization, and/or the like.

The computing system may generate an adjusted OR layout based on the monitor data, the procedure plan, and/or the procedure data.

FIG. 29 illustrates example processing associated with monitoring an OR and determining parameters associated with improving performance of surgical procedure(s) and/or maintenance of the OR. As shown, at 37800, monitored data may be obtained. Surgical data may be monitored by a monitoring system, a surgical computing system, a surveillance system, and/or the like. For example, the monitoring system may include an HCP monitoring system 20002, 20003, or 20004 as described herein with respect to FIGS. 1-3 . The monitoring system may be included in the surgical computing system. The monitoring system may monitor data associated with an OR. The monitored data may include data associated with one or more surgical procedures. The surgical procedures may take place in an OR or multiple ORs. The monitored data may include data associated with HCP, the patient, surgical instruments, surgical equipment, and/or surgical devices. The monitored data may include data associated with positioning. The monitoring system may monitor data associated with the surgical procedure, such as, for example, surgical access location(s) and/or trocar placement(s). The monitored data may be continuously gathered and communicated prior to, during, and/or after a surgical procedure.

The monitoring system may include an OR room imaging system. The monitoring system may include one or more sensing systems, for example, such as the surgeon sensing systems 20020 as described herein with respect to FIG. 2 . The surgeon sensing systems may be worn by HCPs. The surgeon sensing systems may monitor biomarkers associated with the HCPs. The sensing system(s) may include a patient sensing system. The patient sensing system may be worn by the patient, for example. The patient sensing systems may monitor biomarkers associated with the patient.

An environment, such as the environment in an OR, may be monitored. The one or more sensing systems may include an environmental sensing system. The environmental sensing system may include a camera, which may be the set of cameras 20021 as described herein in FIG. 2 . The environmental sensing system may include a microphone, which may be the set of microphones 20022 as described herein in FIG. 2 . The environmental sensing system may include other sensors that may be deployed in the operating room. For example, the environmental sensing system may include camera(s), microphone(s), and/or other sensors that may be deployed in the OR. For example, the monitoring system may include OR room imaging systems, surgeon sensing systems, patient sensing systems, and/or environmental sensing systems.

For example, the monitoring system may include RF systems. The RF systems may be smart and self-identifying. For example, RFID tags may be used. RFID tags may be used to identify HCPs. RFID tags may be used to determine an HCP location. RFID tags may be used to identify a surgical instrument. RFID tags may be used to identify a surgical instrument location.

The monitoring system may monitor data associated with HCPs within an OR. The HCP monitored data may include data associated with HCP motions and movement, positioning, activities, emotions, staffing, biomarkers and/or the like. For example, the HCP monitored data associated with HCP motions and movement may include peripheral movement of the body, such as the HCP(s) arms and torso, and/or gross movement throughout the OR. The monitored HCP data associated with gross movement throughout the OR may include movement around the OR and/or entering or exiting an OR. For example, the HCP monitored data associated with HCP activities may include HCP activity intensity and/or activities performed. For example, the HCP monitored data associated with HCP emotions may include emotional behaviors in an OR, such as HCP expressions and/or HCP interactions. For example, the HCP monitored data associated with staffing may include the number of HCPs and/or surgical staff within an OR for a surgical procedure and/or procedural step. The HCP monitored data may include data associated with the flow of product and activities throughout the surgical procedure.

The HCP monitoring system may monitor data associated with an HCP within the OR. The HCP monitoring system may monitor data associated with the HCP's positioning within the OR. The monitored data associated with HCP positioning may include the location of the HCP within the OR. The monitored data associated with HCP positioning may include the posture of the HCP. The monitored data associated with HCP positioning may include characteristic(s) of the HCP, such as height, arm length, hand shape, hand length, waist width, shoulder width, age, and/or the like, for example. The monitored data associated with HCP positioning may include head or eye position of the HCP. The head or eye position of the HCP may include angle(s) of viewing, such as the direction the HCP is looking, for example.

The HCP monitoring system may monitor data associated with a patient, such as patient positioning within the OR. The monitored data associated with patient positioning may include characteristic(s) of the patient, such as height, weight, waist height, shoulder height, and/or the like, for example. The monitored patient positioning data may include the patient's position on a bed in the OR. The monitored patient positioning data may include the patient's location within the OR. The monitored patient positioning data include the patient's location relative to an HCP's location within the OR. The monitored patient positioning data may include the location of a trocar place on the patient.

The HCP monitoring system may monitor data associated with surgical equipment within the OR. The surgical equipment may include surgical instruments, surgical devices, robotic surgical equipment, and/or the like. The surgical devices may include surgical access device(s). The HCP monitoring system may monitor data associated with surgical equipment positioning within the OR. The HCP monitoring system may monitor data associated with an operating table, such as the operating table 20024 as described herein with respect to FIG. 2 . The HCP monitoring system may monitor data associated with surgical tables and/or surgical trays, such as mayo stands, for example. For example, the HCP monitoring system may monitor data associated with movement of surgical instruments.

The HCP monitoring system may monitor data associated with a visual display, such as a surgical display. For example, the monitored data may include data associated with visual display positioning. The visual display positioning data may include visual display location and/or visual display angle. The monitored visual display positioning data may include display setting(s) associated with the visual display, such as one or more of brightness, color temperature, color contrast, and/or font associated with the visual display.

For example, the HCP monitoring system may perform object detection. The HCP monitoring system may perform object detection to track objects, for example, within an OR. Moving object detection may be performed to recognize the physical movement of a person or an object in a given place or region. By acting segmentation among moving objects and stationary area or region, the moving objects motion could be tracked and thus could be analyzed later. Moving object detection may be performed via background subtraction, frame differencing, temporal differencing, and/or optical flow analysis.

For example, the HCP monitoring system may use RF systems to locate HCPs and surgical equipment in the OR. The RF systems may be smart and self-identifying RF systems. HCPs, instruments, equipment, and/or boundaries may be located using spatial identifying sensors. The locations of HCPs, equipment and/or boundaries may be tracked with respect to the room and/or with respect to the patient, via wireless sensors and beacons. RFID tags may be affixed onto instruments and/or HCPs. A surgical instrument or HCP may be associated with a unique RFID identification. Based on the RFID tags, the location of surgical instruments and HCPs may be monitored and/or tracked.

For example, the HCP monitoring system may monitor data associated with an OR before a surgical procedure. The HCP monitoring system may monitor location, movement, and/or orientation of various surgical equipment and HCPs in the OR. For example, a gyroscope or 3 axis accelerometers may be used to determine orientation and position.

For example, the HCP monitoring system may record a surgical procedure, such as a laparoscopic procedure, for example. The HCP monitoring system may record a surgical procedure using camera(s) and/or microphone(s).

The monitoring system may monitor data associated with the OR layout. For example, the OR layout monitored data may include data associated with surgical equipment, surgical instrument, HCP station(s), camera(s), display(s), and/or the like.

For example, the OR layout monitored data may include data associated with surgical equipment, such as positioning data. Surgical equipment positioning data may include surgical table positioning, operating bed positioning, camera positioning, display positioning, and/or the like. The operating bed may be the operating table 20024 as described herein with respect to FIG. 2 . The OR layout monitored data associated with surgical instrument positioning may include the mix of surgical instruments located in the OR, which may include replacement surgical instruments.

For example, the OR layout monitored data may include data associated with surgical instrument(s). Data associated with surgical instruments may include surgical instrument mix, surgical instrument replacements, surgical instrument positioning, surgical instrument exchanges, surgical instrument usage, and/or the like. For example, surgical instrument mix may be the types and/or number of surgical instruments available for use in the OR and/or for a surgical procedure. For example, surgical instrument positioning may include the location of the surgical instruments within the OR. Surgical instrument positioning may include the orientation of the surgical instrument, for example, during use. For example, surgical instrument exchanges may be monitored, such as the handing off of surgical instruments between HCPs. In examples, the number of surgical instrument handoffs between HCPs may be monitored. For example, a surgical instrument usage may be monitored, such as the duration of use. Surgical instrument readiness may be monitored. For example, surgical instrument readiness may include whether the surgical instrument is within the OR for use and/or prepared for use (e.g., removed from packaging, sterilized).

FIG. 30 shows an example OR layout and HCP activity during surgical procedure that may be generated based on the monitored data. As shown in FIG. 30 , the OR 37650 may include HCPs, surgical equipment, and/or the like. The HCPs in OR 37650 may include a surgeon 37652, anesthesiologist 37654, circulating nurse 37656, and/or scrub nurse 37658. The OR 37650 may include surgical equipment such as an operating table 37660 and/or HCP equipment tables. The HCP equipment tables may include surgeon equipment table(s) 37662 a, 37662 b, and 37662 c, anesthesiologist equipment table(s) 37664 a and 37664 b, circulating nurse equipment table(s) 37666 a and 37666 b, and/or scrub nurse equipment table(s) 37668 a and 37668 b.

The computing system may obtain HCP gross movement data throughout the surgery, for example, as shown in FIG. 30 . During a surgical procedure, the HCPs may travel between equipment stations and the surgical access site, which may be on the patient on the operating table 37660, for example. For example, as shown at 37670, the cumulative displacement for the HCPs during the procedure may be calculated based on the monitored data. The cumulative displacement graph 37670 may illustrate the total gross movement of HCPs throughout the procedure. The computing system may determine downtime and/or wait times during a surgical procedure based on monitored data. Downtime and/or wait times may be experienced, for example, if the HCPs are delayed waiting on test results. For example, delays may be experienced based on pathology wait times checking biopsies and/or margins to determine whether resection is required in a procedure. For example, downtime and/or wait times may be experienced based on equipment failure. For example, the surgical computing system may determine downtime and/or wait times based on delays inconsistent with the surgical procedure plan. For example, as shown at 37672, downtime and/or wait times may be indicated for the HCPs during the surgical procedure. The downtime and/or wait time may be indicated, for example, based on one or more of equipment wait time, procedure wait time, delay time, and/or the like. Graph 37674 shows the calculated ergonomic risk factor for the HCPs during a surgical procedure. The monitored data may include data associated with HCP positioning. The computing system may determine ergonomic risk based on the data associated with HCP positioning. For example, the computing system may calculate a high ergonomic risk factor where the monitored data indicated awkward HCP positioning.

A procedure plan for a surgical procedure may be obtained. The surgical procedure plan may include details associated with the surgical procedure, such as, for example, recommendations for steps for the surgical procedure, instrument mix, number of HCPs for the procedure, duration for the procedure and/or procedure steps, surgical access locations, trocar placements, and/or the like.

Monitored data may be obtained (e.g., received, generated, or the like), for example, by the surgical computing system (e.g., as shown at 37800 in FIG. 29 ). Monitored data from previous surgical procedure(s) may be obtained. The previous surgical procedure(s) monitored data may include data associated with instrument mix, surgical site access locations, OR layout, staffing, trocar placement, and/or the like, from the previous surgical procedure(s).

Referring back to FIG. 29 , at 37802, the surgical computing system may determine procedure data. The procedure data may be associated with the surgical procedure plan. For example, the surgical computing system may determine procedure data such as the duration of the surgical procedure and/or procedure steps, procedure steps performed, inactivity and/or downtime during the procedure, and/or the like. For example, the surgical computing system may determine whether the HCP(s) have acted consistent with the surgical procedure plan based on one or more of the monitored data, surgical procedure data, and/or surgical procedure plan. For example, the surgical computing system may determine that a procedure step was skipped. For example, the surgical computing system may determine that a procedure step was performed untimely. For example, the surgical computing system may determine that a procedure step was performed improperly. For example, the surgical computing system may determine that a procedure step was repeated.

At 37804, adjustment parameter(s) may be determined. The surgical computing system may determine adjustment parameter(s), for example, based on the monitored data and/or procedure plan data. The adjustment parameters may be associated with adjustments to positioning, HCP movement, HCP activity, HCP emotions, surgical instruments, and/or the like. The surgical computing system may determine adjustment parameters(s), for example, to improve the flow of activities performed during the surgical procedure, reduce movement throughout a surgical procedure, reduce possible contamination within an OR, reduce OR turnaround time between procedures, improve efficiency for a surgical procedure, increase HCP focus during the surgical procedure, and/or the like. As those skilled in art may appreciate, various optimization models, simulation models and/or process models may be used in the determination. For example, the surgical computing system may determine adjustments parameters for a surgical instrument mix, surgical access location, OR layout, and/or HCP staffing based on data and/or metadata associated with previous procedures.

As described herein with respect to FIG. 28 , a surgical procedure may be evaluated, for example, based on efficiency and/or outcome success. Efficiency may be associated with the duration a surgical procedure takes for completion, which may include equipment wait times, instrument exchange times, procedure wait times, and/or the like. For example, surgical procedures may be more efficient if there are lower equipment wait times, instrument exchange times, and/or procedure wait times. Efficiency may be associated with gross movement throughout a procedure. For example, less cumulative displacement may result in a more efficient surgical procedure. Surgical procedures may be compared with historic surgical data to determine a comparison with a baseline score.

For example, the surgical computing system may determine adjustment parameter(s) associated with positioning, such as adjustments for OR layout, surgical equipment positioning, surgical instrument positioning, surgical site access, trocar positioning, and/or the like. Adjustments for OR layout may include adjusted positioning for surgical equipment, surgical instruments, cameras, displays, and/or the like. Surgical equipment may include surgical tables, which may be designated to specific HCPs.

FIG. 31 illustrates an adjusted OR layout for the surgical procedure that may be generated by the surgical computing system. As shown in FIG. 31 , the modified OR layout may include HCPs, surgical equipment, and/or the like. The HCPs in OR 37700 may include a surgeon 37702, anesthesiologist 37704, circulating nurse 37706, and/or scrub nurse 37708. The OR 37650 may include surgical equipment such as an operating table 37710 and/or HCP equipment tables. The HCP equipment tables may include surgeon equipment table(s) 37712 a, 37712 b, and 37712 c, anesthesiologist equipment table(s) 37714 a and 37714 b, circulating nurse equipment table(s) 37716 a and 37716 b, and/or scrub nurse equipment table(s) 37718 a and 37718 b.

For example, the surgical computing system may determine adjustment parameters associated with surgical equipment positioning. The surgical computing system may receive monitored data associated with HCP movement throughout the OR. As shown in FIG. 30 , HCP(s) may travel between a surgical equipment table and the surgical access site multiple times throughout a procedure. Based on the monitored data, the surgical computing system may determine an adjusted HCP equipment table position, which may be located closer to the surgical access site.

For example, the surgical computing system may determine an adjusted positioning for the scrub nurse equipment tables 37718 a and 37718 b. The adjusted position may be closer in location to the surgeon, the surgeon equipment tables, and/or the surgical access site. The adjusted HCP equipment positioning, based on the proximity to the surgical access site, may reduce movement throughout the procedure. Improvements to equipment placement may reduce inefficient movement of HCPs and instruments, which may improve the movement flow of the OR.

For example, the surgical computing system may determine adjustment parameters for surgical equipment positioning such that HCP movement paths do not intersect. As shown in FIG. 31 , the surgical computing system may determine adjusted positions for the circulating nurse equipment tables 37716 a and 37716 b. The adjusted circulating nurse equipment table positions may be located in the OR such that the anesthesiologist 37704 does not cross paths with the circulating nurse 37706 during the procedure. Reducing movement intersection may improve movement efficiency during the surgical procedure.

For example, the surgical computing system may determine adjustment parameters associated with surgical site access positioning. The surgical computing system may receive monitored data associated with trocar use and positioning, surgical procedure type, patient body type, co-morbidities, instrument exchanges, and/or the lake. Based on the monitored data, the surgical computing system may determine adjustment parameters such as adjusted trocar angulations, for example. The surgical computing system may determine adjustment parameters such as adjusted access ports, for example.

Based on the modified positioning of the OR layout, the OR 37700 in FIG. 31 may allow surgical procedures with higher efficiency and/or outcome success compared to the OR 37650 in FIG. 30 . For example, OR 37700 may reduce cumulative displacement (e.g., as shown at 37720), down time and/or wait time (e.g., as shown at 37722), and/or ergonomic risk factors (e.g., as shown at 37724). Cumulative displacement may be reduced, for example, based on OR 37700 having surgical equipment positioning such that unnecessary movement is avoided. For example, OR 37700 may allow surgical procedures to be performed faster, for example, based on reduced equipment wait time, instrument exchange time, procedure wait time, and/or the like. Thus, the modified OR layout 37700 may increase the efficiency and/or outcome success of the surgical procedure.

Turning back to FIG. 29 , at 37806, the adjustment parameters may be communicated, for example, to systems within the OR. For example, the surgical computing system may generate a control signal based on the positioning parameter(s). The control signal may be communicated to systems in the OR, and the system may modify their operation(s) based upon the received adjustment parameters. The control signal may be configured to perform adjustments. The control signal may include adjusting a surgical camera location and/or adjusting an angle of view. The control signal may include an indication suggesting an adjustment to HCP's movement within the OR. For example, the adjustment parameters may be presented.

Surgical site infection may be a health problem. The surgical computing system may determine that surgical site infection risk may increase, for example, if environmental contamination is present in the OR. Environmental contamination may occur based on traffic in the OR. The HCP movement data may include HCP traffic in an OR such as door opening, movements, the number of persons inside the OR during the surgical procedure, and/or the like. Environmental contamination, such as air and/or wound contamination, may be reduced, for example, if traffic within the OR is minimized.

For example, the surgical computing system may determine adjustment parameter(s) associated with reducing possible contamination of the OR. The surgical computing system may obtain monitored data associated with HCP movement, for example, that may indicate potential environmental contamination. The HCP movements may include movements that may lead to environmental contamination. Based on the monitored data, the surgical computing system may determine adjustment parameters associated with a limit on HCP movement during a procedure, a limit on door opening, a limit on the number of HCPs inside the OR during the surgical procedure, and/or the like.

The surgical computing system may determine adjustment parameter(s) associated with modifying HCP actions, for example, based on monitored data and/or procedure data. For example, the surgical computing system may obtain monitored data and/or surgical procedure data associated with pre-procedure steps and/or post-procedure steps. The surgical computing system may track OR turn over time between surgical procedures. Based on the turnover time, the surgical computing system may determine how efficiently an OR has been prepared (e.g., cleaned, cleared, and restocked) for the next surgical procedure. The surgical computing system may determine that a procedure step has been performed improperly based on the monitored data. Based on the determination that the procedure step has been performed improperly, the surgical computing system may determine that the procedure step must be redone. The surgical computing system may determine that a procedure step has been performed untimely. Based on the determination that the procedure step has been performed untimely, the surgical computing system may allocate more staff to performing the procedure step.

For example, the surgical computing system may determine that the OR was improperly prepared for the next surgical procedure. The next surgical procedure may involve using a surgical instrument, such as a surgical stapler, for example. The surgical computing system may determine, based on monitored data, that the surgical stapler was not prepared and/or was not located in the OR. Based on the determination that the OR was improperly prepared, the surgical computing system may notify staff about the failed preparation. The surgical computing system may notify the staff to prepare the surgical stapler before the surgical procedure.

For example, the surgical computing system may determine that the OR was inefficiently cleaned after a surgical procedure. The surgical computing system may receive monitored data associated with the staff cleaning the OR after the surgical procedure. The monitored data may indicate that cleaning steps were repeated. The surgical computing system may determine that the repeated cleaning steps were not needed to properly clean the OR. The surgical computing system may notify the staff that the repeated step was not necessary, for example, to improve the efficiency of the cleaning procedure. For example, the surgical computing system, based on the monitored data, may determine that a cleaning step is being repeated. Based on the determination, the surgical computing system may notify the staff performing the repeated step to stop.

The surgical computing system may determine adjustment parameters associated with the number of HCPs for a surgical procedure. For example, the surgical computing system may receive monitored data associated with the number of HCPs in an OR and/or HCP activity levels during a surgical procedure. The surgical computing system, based on the monitored data and/or biomarker data (e.g., as described herein), may determine a modified number of HCPs in the OR for the surgical procedure. The modified number of HCPs may be an increase or decrease in the number of HCPs for the surgical procedure. For example, the surgical computing system may compare the HCP activity intensity with one or more threshold intensity levels to determine the need for more or less staff for the surgical procedure. HCP activity intensity may be determined based on HCP stress levels and/or HCP inactivity. For example, HCP activity intensity may be low if an HCP is idle and/or not performing activities. For example, HCP activity intensity may be high if an HCP is experiencing stress.

For example, the surgical computing system may determine to reduce the number of HCPs for a surgical procedure. The surgical computing system may determine to reduce the number of HCPs for a surgical procedure, for example, if the surgical procedure is determined to be overstaffed based on the monitored data. A surgical procedure may be overstaffed, for example, if there are HCPs in the OR that are idle and/or not performing activities. A surgical procedure may be determined to be overstaffed, for example, if the surgical procedure may be performed with fewer HCPs than are present. For example, a surgical computing system may determine to reduce the number of HCPs for a surgical procedure, for example, if HCP activity levels fall below a threshold. HCP activity levels may fall below a threshold, for example, if the HCPs have downtime or are inactive for a predetermined duration of time throughout the surgical procedure.

The surgical computing system may determine to increase the number of HCPs for a surgical procedure, for example, if the surgical procedure is determined to be understaffed based on the monitored data. A surgical procedure may be understaffed, for example, if there are not enough HCPs in the OR to perform the surgical procedure. The surgical procedure may be determined to be understaffed, for example, if HCP activity intensity and/or HCP stress levels are high. The surgical computing system may determine to increase the number of HCPs for a surgical procedure, for example, if HCP activity levels exceed a threshold.

Staff utilization may be monitored throughout a surgery. A first procedural step within a surgical procedure may require more HCP staff than a second procedural step. The surgical computing system may continuously monitor the surgical procedure to determine staffing needs for a particular procedural step. For example, a surgical computing system may determine that a first surgical procedure step is overstaffed and may determine that a second surgical procedure step is understaffed. The surgical computing system may determine, based on completion of a procedural step and/or task, to reduce the number of HCPs, for example, because the HCP is no longer needed. The surgical computing system may determine, based on the start of a procedural step and/or task, to increase the number of HCPs.

For example, based on the determination to modify the number of HCPs in the OR, the surgical computing system may indicate or give a notification to the OR. If the surgical computing system determines to reduce the number of HCPs in the OR, a notification may be given to certain HCPs to leave the OR. If the surgical computing system determines to increase the number of HCPs in the OR, a notification may be given to HCPs to enter the OR.

For example, the surgical computing system may determine adjustment parameter(s) associated with surgical instruments, such as surgical instrument mix, surgical instrument exchanges, surgical instrument usage, and/or the like. For example, the surgical computing system may determine a recommended surgical instrument for a surgical procedure and/or procedure step. The surgical computing system may determine recommended surgical instrument(s) to improve instrument to job correlation. The surgical computing system may determine recommended surgical instrument(s) to anticipate an unexpected need for a surgical instrument within a surgical procedure.

For example, the surgical computing system may receive monitored data associated with surgical instrument exchanges. The surgical computing system may track surgical instrument exchanges relative to the surgical procedure and/or task and the duration elapsed to accomplish the surgical procedure. For example, the surgical computing system may track instrument exchanges between surgical instruments having a similar function, such as Bipolar RF, Monopolar RF, and/or Ultrasonic advanced energy devices. The surgical computing system may relate the surgical instruments to the time it takes to complete a surgical task. The surgical computing system may perform video analysis of the procedure steps to determine the efficiency of an energy device in accomplishing a surgical task, such as a dissection or transection task, for example.

Based on the monitored data, the surgical computing system may determine recommended surgical instruments, such as a combination of devices for a surgical procedure and/or complication. The recommended surgical instruments may improve the efficiency or efficacy of the surgical procedure. The surgical computing system, for example, may determine recommended instrument mixes that improve efficiency, such as decreasing the time to perform a surgical task, but maintain surgical outcomes. For example, the surgical computing system may determine recommended surgical instruments based on monitored sealing/oozing performance of a surgical instrument over time. For example, the surgical computing system may determine recommended surgical instruments based on proximity to adjacent structure for safety, such as managing thermal spread, and efficiency for future procedure steps. In examples, the surgical computing system may determine recommended surgical instruments to dissect fatty tissue with speed, for example, because vital organs are far away from the surgical site. In examples, the surgical computing system may determine recommended surgical instruments to perform fine dissecting to expose vessels with precision and/or safety, for example, based on proximity to structures. In examples, the surgical computing system may determine recommended surgical instruments to transect vessel(s) based on sealing performance.

For example, the surgical computing system may monitor surgical instrument mix and replacements. The surgical computing system may determine the efficiencies of the various mixes of instruments' impact on access, instrument exchanges, instrument utilization, and/or time to complete the procedure based on monitored data associated with previous procedures. Based on the determined efficiencies, the surgical computing system may determine a recommended surgical instrument mix. The determined recommended surgical instrument mix may decrease the time to complete the procedure.

The surgical computing system may determine recommended surgical instruments based on an anticipated need during a detected surgical complication, for example, to minimize delays to the surgical procedure. For example, the computing system may identify a certain surgical instrument, adjunct therapy, certain surgical device(s), and/or surgical product for treating detected surgical complication. The identified surgical instrument that may treat the surgical complication, for example, may be outside of the surgical procedure plan.

For example, the surgical computing system may receive monitored data associated with a surgical procedure. The monitored data may include surgical instrument usage and/or adjunct treatment usage. The surgical computing system may determine, based on the monitored data and/or procedure plan, recommended surgical instruments, adjunct therapies, surgical devices, surgical products, and/or the like, for example, to minimize the unexpected need within a procedure.

For example, the surgical computing system may determine to have a backup surgical instrument in the event of a surgical complication. The surgical computing system may anticipate the need for a backup surgical instrument based on aggregating or compiling past procedures, co-morbidities, biomarker monitoring, and/or imaging. For example, the surgical computing system may determine that a surgical procedure combined with certain biomarker measurements may lead to a surgical complication. Based on the anticipated surgical complication, the surgical computing system may determine recommended surgical instruments that otherwise may have been unanticipated. Determining the recommended surgical instruments may minimize the need to retrieve an unanticipated product, which may result in delaying the procedure.

For example, the surgical computing system may identify repeatedly used alternative products and/or additional product that may be needed for a procedure, based on monitored data associated with previous surgical procedures. The surgical computing system may determine to add additional product that may be needed for the procedure and/or to stock the repeatedly used alternative product in an OR backup storage location. For example, the surgical computing system may determine primary suggestions and backup alternative combination suggestions based on lacking device inventory. The surgical computing system may receive monitored data associated with the OR setup for a surgical procedure. The OR setup data may include the surgical instrument mix intended for use in the procedure and the instrument mix within the local backup storage. The surgical computing system may determine recommended surgical instruments for the instrument mix intended for use in the procedure and the instrument mix in the local backup storage such that surgical instruments that may be needed for the procedure, including anticipated surgical complications, can be provided.

For example, a surgical complication may call for treatment by a unique device, which may be unavailable. The surgical computing system may determine recommended surgical instruments, such as device combinations and/or approaches, to achieve the same surgical outcome as if the unique/ideal device was used.

The surgical computing system may determine parameters associated with a surgical instrument anticipated for future use in a procedure, for example, based on monitored data and/or procedure data. For example, the surgical computing system may determine the readiness of surgical instruments for use when needed in the procedure. For example, the surgical computing system may determine that a surgical instrument will be used in the next procedural step based on the surgical procedure plan. The surgical computing system may anticipate surgical procedure steps and the need for a surgical product in a ready-to-use state for the anticipated steps.

The surgical computing system may determine that the surgical instrument is not prepared (e.g., in a ready to use state), for example, based on the monitored data. The surgical computing system may indicate, based on the determination that the surgical instrument is not prepared, to HCPs to prepare the surgical instrument. The indication may be configured to prompt the HCPs to prepare the surgical instrument before it is needed for the anticipated step, which may prevent delays in the procedure. In examples, the surgical computing system may determine that the surgical instrument is not present within the OR, for example, based on the monitored data. The surgical computing system may indicate to HCPs, based on the determination that the surgical instrument is not present within the OR, to retrieve the surgical instrument. Retrieving the surgical instrument before the anticipated steps may prevent delays in the procedure.

The surgical computing system may determine parameters associated with reducing inactivity and/or downtime within an OR. For example, a surgical computing system may monitor downtime and inactivity within the OR. The surgical computing system, based on the monitored downtime and inactivity within the OR and/or procedure data, may determine parameters associated with reducing wait times during a surgical procedure. The surgical computing system may determine that inactivity and/or downtime within the OR is inconsistent with the surgical procedure plan. For example, inactivity and/or downtime may be inconsistent with the surgical procedure plan if the inactivity exceeds a predetermined time threshold.

The surgical computing system may determine downtime and inactivity in the OR if the surgical computing system detects that the OR is waiting on results or for other jobs to be completed before moving onto the next procedural step. For example, inactivity may occur based on pathology wait times from checking biopsies and/or margins to determine a next procedural step, such as determining whether resection is needed and/or ensuring enough resection is performed.

The surgical computing system may determine downtime and inactivity based on detected equipment failure. For example, equipment failure, such as monitoring equipment failure, may delay the surgical procedure and impact patient flow and/or resource utilization. To prevent equipment failures, the surgical computing system may determine maintenance schedules and/or replacement schedules that may reduce inactivity resulting from failure during the surgical procedure. For example, the surgical computing system may receive monitored data and/or procedure data. The monitored data and/or procedure data may indicate the types, frequency, and/or times that equipment failure occurs. Based on the types, frequency, and/or times that the equipment failure occurs, the surgical computing system may determine maintenance schedules or schedule replacements for the surgical equipment, for example, to prevent the failures from occurring.

Equipment failures may occur, for example, based on incorrect setup. The surgical computing system may receive monitored data associated with OR setup, HCP reactions and/or facial responses, and the like. The surgical computing system may, based on the monitored data and procedure data, identify errors associated with incorrectly setup equipment. The surgical computing system, based on the identified errors, may notify or provide indication to staff members, for example, to intervene, train, and/or confirm setup prior to surgery.

The surgical computing system may determine parameters associated with running a simulator and/or test run, for example, to prevent equipment failures and reduce the resulting downtimes. A simulator may be run after equipment is setup, for example, to perform a test run to confirm, prior to a surgical procedure, that no errors with the equipment will occur. For example, the simulator may include sequencing energy devices through a normal operation at a power level that does not cause harm to anyone or the surroundings. For example, an RF energy device may activate energy, with voltage and current at the lowest setting, to confirm that a signal was received.

Downtime and inactivity in the OR may occur based on a lack of proper planning, deficiencies in teamwork, communication gaps, limited availability of trained support staff, and/or the like. The surgical computing system may determine an inactivity in the OR inconsistent with the surgical procedure plan, for example, based on the monitored data and/or procedure plan. The procedure plan may indicate that the procedural step should be performed within an allotted time. The surgical computing system may determine an inactivity inconsistent with the surgical procedure plan, for example, if the procedural step is taking longer to complete than the allotted time. The surgical computing system may generate an indication of inactivity inconsistent with the surgical procedure plan. The surgical computing system may determine a recommendation associated with the inactivity inconsistent with the surgical procedure plan.

For example, the surgical computing system may determine a recommendation to use a playbook and/or an app/tablet based on the type of surgical procedure. The playbook and/or app/table may provide an overview of the procedure to staff members prior to surgery indicating to staff member one or more of responsibilities, sequence of actions, equipment setup steps, troubleshooting for common errors/issues, and/or the like. The playbook and/or app/table may ensure the team is prepared and is aware of the roles and responsibilities for the surgical procedure. Whether tasks are performed properly may be monitored. The surgical computing system may determine that a task was performed improperly, such as the task was skipped, performed in the wrong order, and/or performed untimely, based on the monitored data. For example, a surgical task may have been skipped if the surgical procedure plan calls for a step to be taken but an analysis of the monitored data indicates the task was not performed. For example, the surgical task may have been performed improperly if the monitored data indicates that tasks were performed in the incorrect order. The surgical computing system may generate indications associated with audible, visual, and/or haptic feedback to the staff in the OR.

Downtime and inactivity in the OR may occur based on patient positioning for a surgical procedure. Prior to surgery the patient may be transferred to the operating table. The final positioning of the patient may be performed based on planning and coordination by HCPs. The HCPs may take time prior to the surgery to determine the final positioning of the patient. Delays may occur based on patient repositioning during a surgical procedure.

For example, the surgical computing system may receive monitored data and/or surgical procedure plan, such as patient characteristics/profile, surgical procedure type, OR layout, equipment positioning, and/or the like. Based on the monitored data and/or surgical procedure plan, the surgical computing system may determine a recommendation associated with the optimal patient position on an operating bed. The patient positioning recommendation may reduce setup time by avoiding having the OR team plan and coordinate such that the HCPs may direct focus to other tasks. The patient positioning recommendation may reduce downtime and/or inactivity that may have occurred from improper patient positioning leading to repositioning.

The surgical computing system may determine parameters associated with altering emotions experienced by HCPs in the OR. Surgery may be a high stress environment which may cause individual emotional impact to HCPs or between HCPs. The stress may cause distractions, loss of focus, resentment, lack of communication, lack of teamwork, negative impacts towards team members, and/or the like, which may delay and/or impact surgery response times and/or outcomes. The surgical computing system may determine parameters associated with alleviating negative emotions that may occur during a surgical procedure.

For example, the surgical computing system may receive monitored data such as OR staff emotional state. The OR staff emotional state may indicate a stressful environment. The OR emotional state may include expressions or interactions with other HCPs. The surgical computing system may determine parameters associated with altering emotions in the OR. For example, the surgical computing system may determine adjustment parameters and/or generate control signals associated with altering emotions in the OR. The adjustment parameters and/or control signals include adjusting audio and/or visual devices. For example, the surgical computing system may determine parameters adjusting audio devices within the OR, such as playing and/or modifying music or sounds. The modified music or sounds in the OR may be directed at specific HCPs. The music or sounds in the OR may include meditation sounds, which may calm the room.

For example, the surgical computing system may determine parameters adjusting visual displays, such as to providing a visual aid. The visual aid may momentarily distract and improve the mood in the OR. The visual aid may include positive reinforcement played throughout the OR. The visual aid may be displayed on non-critical monitors. The surgical computing system may determine to provide indication or give a notification to staff outside the OR. The indication/notification may include a recommendation to pull team members together after a surgical procedure to resolve conflict, such as resentment.

For example, the surgical computing system may receive monitored data such as signs of fatigue in the OR. The surgical computing system may determine parameters associated with reducing the fatigue, such as playing music in the OR. The surgical computing system may determine to adjust the music in the OR, such as speeding up or slowing down the tempo of the music. The surgical computing system may determine parameters associated with the light to alter the environment and behavior within the OR.

The computing system may monitor healthcare professionals in a surgical procedure and provide parameters associated with improving motions and/or postures of the HCPs. The parameters associated with improving motions and/or postures of the HCPs may be included in recommendations, adjustments, and/or feedback. The parameters may be associated with ergonomic positioning.

For example, a computing system may monitor surgeon motion, posture, and surgical access and generate recommendations to reduce wear on HCPs. The motions and postures of HCPs monitored throughout surgical procedure(s) may be analyzed. Improvements for posture, weight lifting, standing, and the like may be identified.

The computing system may record one or more of patient position, surgeon access location, and surgeon access orientation. The system may analyze one or more of the patient position, surgeon access location, and surgeon access orientation. The computing system may record and analyze one or more of the patient position, surgeon access location, surgeon access orientation, and/or the like. The computing system may record and analyze one or more of the patient position, surgeon access location, surgeon access orientation and/or the like to generate one or more adjustment parameters. The adjustment parameters may reduce repositioning and awkward positions and postures. The adjustment parameters may include one or more of instrument mix selection, trocar location, OR table setup, patient positioning, and/or the like.

For example, the computing system may receive monitored data associated with an operating room. The monitored data may include data associated with one or more of OR layout, surgical equipment location, patient positioning, surgical instrument mix, surgical device positioning, HCP motion(s), HCP posture(s), physical trait(s) of HCP(s), the head and/or eye position(s) of HCP(s), or surgical display positioning. The computing system may determine one or more ergonomic adjustment parameters associated with ergonomic positioning within the operating room based on the monitored data. The ergonomic adjustment parameter(s) may include adjustments to one or more of OR layout, patient positioning, surgical display operation, surgical equipment location and/or the like. The computing system may send an indication of the ergonomic adjustment parameter(s). The computing system may communicate the ergonomic adjustment parameter(s) associated with ergonomic positioning to one or more systems associated with the operating room. For example, the computing system may communicate the adjustment parameter(s) to a system configured to control surgical display(s) in the OR. The surgical display may present the ergonomic adjustment parameters. The system configured to control surgical display(s) may modify the positioning or settings of one or more surgical display(s), for example, based on the ergonomic adjustment parameters.

The computing system (e.g., a surgical computing system) may include a surgical hub 20002 as described herein with respect to FIG. 2 . For example, the surgical computing system may include at least one of the following: a surgical hub 20006 in communication with a cloud computing system 20008, for example, as described in FIG. 2 . A surgical computing system may include at least one of the following: a surgical hub 20006 or a computing device 20016 in communication with a could computing system 20008. The cloud computing system 20008 may include at least one remote cloud server 20009 and at least one remote cloud storage unit 20010. The computing system may be or may include an HCP monitoring system such as the HCP monitoring system 20000, 20002, 20003, or 20004 as described herein with respect to FIGS. 1-3 . The computing system may be a computing system operatively connected to the HCP monitoring system(s) 20000, 20002, 20003, and/or 20004. The computing system may be or may include the computing system 20271 described herein with respect to FIG. 9 . The computing system may be or may include the computer system 20063 described herein, for example, with respect to FIG. 4 .

The surgical monitoring data may be obtained via the surgical hubs. For example, a surgical hub may obtain surgical monitoring data from various sensing systems such as the wearable sensing system(s) 20011, and/or environmental sensing system(s) 20015 described herein with respect to FIG. 1 . The surgical hub may obtain surgical monitoring data from HCP monitoring devices 35510, environmental monitoring devices 35512, patient monitoring devices 5124, and/or modular devices 5102 as described herein with respect to FIG. 11 .

FIG. 32 illustrates example processing associated with monitoring an operating room and determining parameters associated with ergonomic positioning. As shown, at 38110, an HCP monitoring system, which may be an HCP monitoring system 20002, 20003, or 20004 as described herein with respect to FIGS. 1-3 , may monitor data. The HCP monitoring system may monitor data associated with an OR as described herein with respect to step 37800 in FIG. 29 . The monitored data may include data associated with one or more surgical procedures. The surgical procedures may take place in an OR or multiple ORs. The monitored data may include data associated with HCP, the patient, surgical instruments, surgical equipment, and/or surgical devices. The surgical device may include a surgical access device. The monitored data may include data associated with positioning.

At 38112, the HCP monitoring system may communicate the monitored data. The HCP monitoring system may communicate the monitored data to the surgical computing system. The monitored data may be continuously gathered and communicated prior to, during and/or after a surgical procedure.

As shown at 38114, surgical equipment may monitor data. The surgical equipment may be a surgical instrument 20282 as described in connection with FIG. 10 . The surgical instrument 20282 may monitor data, such as user inputs associated with movement and positioning of the surgical instrument, for example. The surgical instrument 20282 may use an acceleration sensor to monitor the movement and positioning of the surgical instrument 20282. The surgical instrument 20282 may monitor the orientation of the surgical instrument 20282. The surgical instrument 20282 may monitor the length of time the surgical instrument 20282 is maintained in a particular position.

For example, the surgical equipment may be a visual display, such as the primary display 20023 as described in connection with FIG. 2 , and/or other displays described herein. The primary display 20023 may monitor data, such as positioning, for example.

At 38116, the surgical equipment may communicate the monitored data to the surgical computing system. The monitored data may be continuously gathered and communicated prior to, during and/or after a surgical procedure.

At 38118, the surgical computing system may obtain monitored data. For example, the computing system may obtain monitored data as described herein with respect to step 37800 in FIG. 29 . The surgical computing system may obtain monitored data from the HCP monitoring system. The surgical computing system may obtain monitored data from surgical equipment. The surgical computing system may obtain monitored data from the HCP monitoring system and surgical equipment.

At 38120, the surgical computing system may process the obtained monitored data. The surgical computing system may determine one or more parameters based at least in part on the obtained monitored data. The monitored data may include OR setup monitoring and/or position and posture monitoring over a surgical procedure. The surgical computing system may determine adjustment parameters associated with ergonomic positioning within the OR. For example, the adjustment parameters may include adjustments associated with an operating room or a surgical procedure. The adjustment parameters may include adjustment(s) to the OR layout, for example, prior to surgery or during surgery. The adjustment parameters may include changes to equipment layout to improve ergonomics of the HCP(s).

For example, the parameters may indicate recommendation(s) for an OR layout prior to surgery. The surgical computing system may obtain monitored data identifying HCP characteristics, for example, prior to starting surgery. The surgical computing system may obtain the monitored data from the HCP monitoring system, which may include a video. The HCP characteristics may include height, arm length, hand shape or length, waist width, shoulder width, age, or focal position of an HCP. Based on the HCP characteristics, the surgical computing system may determine the recommendations for the OR layout prior to surgery. The OR layout recommendations may include table height, for example, for a mayo stand. The OR layout recommendations may include the mayo stand placement and/or angle. The OR layout recommendations may include surgical monitor position and/or angle, for example, to maintain a neutral position or minimize extension or flexion for reach or neck or back strain. The OR layout recommendations include one or more of table height, mayo stand placement and/or angle, surgical monitor position and/or angle, and/or the like.

For example, the surgical computing system may obtain monitored data identifying characteristics of a patient prior to surgery. The surgical computing system may obtain the monitored data from a video, for example. The characteristics of a patient may include height, weight, waist height, and/or shoulder height associated with the patient. Based on the characteristics of the patient, the surgical computing system may determine recommendations for an OR layout prior to surgery. The OR layout recommendations may include patient positioning, such as the position of the patient on the patient bed. The surgical computing system may determine the patient positioning based on the characteristics of the HCP and the patient, for example. The surgical computing system may determine the patient positioning based on the characteristics of the patient relative to the characteristics of the HCP. The surgical computing system may determine the patient positioning based on the characteristics of the HCP, the characteristics of the patient, and a surgical site.

For example, the surgical computing system may obtain monitored data associated with the posture of an HCP, such as a surgeon, during and/or throughout a surgical procedure. The surgical computing system may determine the posture of the HCP based on the monitored data. For example, the surgical computing system may determine that the posture of the HCP is an ergonomic posture. The surgical computing system may determine that the posture of the HCP is a neutral or correct posture. The surgical computing system may determine that the posture of the HCP is an improper or poor posture, such as a straining or awkward posture, for example. A posture of an HCP that is ergonomic, neutral, or correct posture may decrease the wear on the body of the HCP. A posture of an HCP that is an improper or poor posture may increase the wear on the body of the HCP.

The surgical computing system may determine adjustment parameters and/or recommendation parameters associated with the posture of an HCP, for example, based on the determined posture of the HCP. The surgical computing system may determine adjustment parameters and/or recommended parameters that may correspond to a neutral posture.

For example, the surgical computing device may determine adjustment parameters or recommendation parameters associated with a neutral posture of the neck or cervical spine of the HCP. The surgical computing device may determine the position of a display or monitor that corresponds to a neutral posture of the HCP, for example, based on the display's location and/or positioning, the HCP's position and/or the HCP's characteristic(s) described herein. The surgical computing device may calculate adjustment parameter(s) such as raising, lowering, and/or angling the display or monitor. The raising, lowering, or angling the display or monitor may improve the posture of the HCP. The raising, lowing, or angling the display or monitor may reduce strain on the HCP.

For example, the surgical computing device may determine adjustment parameters or recommendation parameters associated with a neutral posture of the mid-back or thoracic spine of the HCP. The surgical computing device may determine the positioning of a table, such as a surgical table or a mayo stand, for example, that corresponds to the neutral posture of the mid-back or thoracic spine of the HCP. The determination may be based on the current positioning of the table, the position of the HCP, and/or HCP's characteristic(s) described herein. The surgical computing device may determine adjustment parameters such as raising, lowering, or angling the table, based on the table position that may result in neutral posture of the mid-back or thoracic spine of the HCP. The surgical computing device may determine adjustment parameters associated with patient positioning that may correspond to the neutral posture. The adjustment parameters may include raising, lowering, and/or angling the position of the patient.

For example, the surgical computing device may determine adjustment parameters or recommendation parameters associated with a neutral posture of the low-back or lumbar spine of the HCP. The surgical computing device may determine the positioning of a table, such as a surgical table or mayo stand, the positioning of a display or monitor, and/or the positioning of a surgical instrument, that corresponds to the neutral posture of the low-back or lumbar spine of the HCP, and may generate adjustment parameters or recommendation parameters accordingly. The determined parameters associated with the recommended positioning of the table, display or monitor, and/or the surgical instrument may minimize or reduce pelvic twist or pelvic tilt. Minimizing or reducing pelvic twist or pelvic tilt may decrease the wear on the HCP.

The surgical computing system may determine parameters associated with positioning of surgical equipment in an OR. The surgical computing system may determine parameters associated with the location of surgical equipment in the OR. The surgical equipment may include a surgical robot, which may be the robotic system 20034 as described herein with respect to FIG. 2 . The robotic system 20034 may include a surgeon's console 20036, a patient side cart 20032, and a surgical robotic hub 20033. For example, the surgical computing system may obtain monitored data associated with a surgical procedure, such as a laparoscopic procedure. The surgical procedure may be recorded. The laparoscopic procedure may use surgical equipment such as a surgical robot, for example. The surgical computing system may determine positioning parameter(s) and/or location parameters associated with the surgical robot based on the monitored data. The parameters may include the positioning of the surgical robot. The parameters may include a surgical robot configuration. The parameters may include the location for the surgical robot. The parameters may include introduction of the surgical robot into the procedure. The introduction of the surgical robot into the procedure may include a surgical robot supplementing a procedure, such as a hybrid procedure. The introduction of the surgical robot into the procedure may include a full surgical robot procedure.

The surgical computing system may determine parameters associated with ergonomic positioning of surgical instruments based on the monitored movement of the surgical instruments. For example, the surgical computing system may obtain monitored data associated with the movement of surgical instruments in the OR. The monitored data may be associated with a laparoscopic procedure. The monitored data may include data associated with a surgical robot. Based on the monitored data associated with the surgical instruments in the operating room, the surgical computing system may determine parameters associated with ergonomic positioning of the surgical instruments.

For example, laparoscopic procedures may be monitored to automate a robot setup for similar procedures using surgical robots. The surgical computing system may determine surgical robot setup parameters for similar surgical procedures based on the monitored data.

For example, surgical instrument use may be analyzed. Surgical instrument use may be analyzed based on the monitored surgical instrument exchange. Surgical instrument use may be analyzed based on the monitored usage amount. Surgical instrument use may be analyzed based on an appropriateness of a surgical instrument use for a procedure. For example, the surgical computing system may analyze surgical instrument use. The surgical computing system may receive monitored data associated with surgical instruments. The monitored data associated with surgical instruments may include surgical instrument movement, surgical instrument usage amount, the type(s) of surgical instrument(s) used for a surgical procedure, and/or surgical instrument exchange(s). The surgical computing system may obtain information associated with an ideal or standard for surgical instrument usage. The surgical computing system may determine parameters associated with the surgical instrument use. For example, the surgical computing system may determine parameters associated with the surgical instrument use based on the monitored data. The surgical computing system may determine surgical instrument use parameter(s) based on the ideal standard for surgical instrument usage. The surgical computing system may determine the surgical instrument use parameter(s) based on the monitored data and the predetermined standard surgical instrument usage value(s). For example, the surgical computing system may identify product mix irregularities based on the monitored data and the standard product use practice and/or value(s). The surgical computing system may determine an overuse or underuse of a surgical instrument, for example, for a surgical procedure by comparing the monitored instrument use and the standard instrument use.

The surgical computing system may determine parameters associated with patient positioning, access, and repositioning, for example, to improve HCP ergonomic requirements. For example, a surgical computing system may obtain monitored data associated with patient positioning, surgical access devices, and repositioning within the OR throughout a surgical procedure. The surgical computing system may determine a modified patient position or surgical access point. The modified patient position may include the initial patient positioning and/or the initial surgical access point for a surgical procedure. The modified patient position and/or the modified surgical access point may minimize or reduce heavy labor and/or overstress of the HCPs.

The position of the patient on the operating table may be determined. Prior to a surgical procedure, a patient may be transferred to an operating table. An OR team may plan and/or coordinate the position of the patient on the operating table. The position of the patient may create delays during surgery, for example, due to stopping the procedure to reposition the patient. The recommended position of the patient may be determined, for example by the surgical computing system, based on one or more of the patient characteristic or profile, the surgical procedure type, the OR room layout, and/or surgical equipment positioning. The surgical computing system determining the recommended position of the patient on the operating bed may reduce setup time, for example, by allowing HCPs or an OR team to plan, coordinate, and/or direct focus to other tasks.

For example, based on the monitored data and the determined recommended position of the patient, the surgical computing system may determine whether the current patient position is proper. The surgical computing system may determine feedback based on the determination of whether the current patient position is proper. For example, feedback to change (e.g., and how to change) the patient positioning may be determined based on an improper positioning. Feedback confirming proper patient positioning may be determined if the monitored data indicates proper positioning. The surgical computing system may indicate the recommended patient positioning by casting an outline for proper positioning of the patient on the operating table.

A surgical computing system may determine patient positioning parameters based on surgical monitoring data. Injuries and complications may be prevented through proper patient positioning throughout a surgical procedure. Proper patient positioning may be determined based on surveillance of an OR team. In examples, the surgical computing system receive monitored data associated with an OR and an OR team. The surgical computing system may obtain monitored data associated with patient positioning in the OR. The surgical computing system may obtain monitored data associated with movements or repositioning of the patient, for example, after general anesthesia is administered. The surgical computing system may determine whether it safe to move a patient based on surgical monitoring data such as the blood pressure and/or blood pressure alteration(s) of the patient. The surgical computing system may indicate that it is safe to move the patient on a condition that monitored data indicates a safe systemic blood pressure.

It may be important for an HCP to manage monitors, intravenous lines, and/or endotracheal tubes when moving a patient. The surgical computing system may receive monitored data associated with the monitors, intravenous lines, and/or endotracheal tubes prior to, during, and after movement of a patient. Based on the monitored data, the surgical computing system may determine parameters associated with modifying the patient positioning in the OR. The surgical computing system may determine parameters associated with changing the patient positioning based on the monitored data, for example, to prevent complications. With the surgical computing system determining the patient positioning needs, the OR team or anesthesiologist may spend focus, energy, and/or time on other tasks.

For example, the surgical computing system may determine a risk level associated with a surgical procedure, for example, based on monitored data or historical data. For example, the surgical computing system may monitor patient positioning and/or surgical devices within an OR, such as intravenous lines and tubes, for example. The surgical computing system may determine a risk level associated with the positioning of a patient and/or surgical devices, for example, based on the monitored data. The determined risk level may be associated with a surgical complication. In examples, an improper positioning of surgical devices may increase the risk level in a surgical procedure. The surgical computing system may determine a risk level to be good, low risk, or high risk. The risk level determined to be good may indicate that a positioning of a surgical device is proper and risk of surgical complication is not a concern. A risk level determined to be low risk may indicate that a positioning of a surgical device has a low risk of surgical complication. A risk level determined to be high risk may indicate that a positioning of a surgical device has a high risk of surgical complication. The surgical computing system may determine parameters associated with the positioning of the surgical devices, for example, based on the monitored data. The parameters may include recommendations for positioning of the surgical devices, for example, to decrease the risk of surgical complication.

The surgical computing system may determine the risk of a particular injury or complication based on the monitored data and potential injuries. A range of injuries may occur if a patient is placed or moved improperly during a surgical procedure or if surgical devices are in improper positions. For example, the injuries may include a peripheral nerve injury and/or a postoperative visual loss.

A peripheral nerve injury may be caused by poorly positioned patients. The peripheral nerve injury may result in minor or serious conditions. For example, a peripheral nerve injury may result in a numb arm. A peripheral nerve injury may result in a serious morbidity. Types of peripheral nerve injuries may include an ulnar injury, a brachial plexus injury, and a spinal cord injury. For example, ulnar injuries may occur. Ulnar injuries may occur during surgery. The ulnar nerve may run along the ulna bone. The ulnar nerve may give sensation to a forearm, fourth finger, and/or fifth finger. If the ulnar nerve is compressed, feeling may be cut off from the area. Compression of the ulnar nerve may occur if there is extreme flexion of the elbow, which may stretch the nerve. For example, brachial plexus injuries may occur. Brachial plexus injuries may occur due to improper positioning of patients during surgery. The brachial plexus may include a network of nerves extending from the spinal cord through the neck and into the armpit. If the brachial plexus is improperly positioned, patients may experience numbness and/or weakness in the upper extremity.

For example, spinal cord injuries may occur. Spinal cord injuries may be a severe peripheral nerve injury. Injury to the spinal cord may occur due to improper placement of a patient's neck during a surgical procedure. Spinal cord injuries may result in one or more of tissues ischemia, pulmonary compromise, and/or compartment syndrome. Tissue ischemia may be a restriction of blood supply to tissues, which may cause a shortage of oxygen necessary to keep tissue alive. Ischemia may occur if a patient is improperly adjusted while lying flat on their back. Pulmonary problems may occur if surgery is performed in the lateral decubitus position. Pulmonary compromise may occur due to movement of abdominal contents and/or the mediastinum, which improve airway movement and increase blood flow. Compartment syndrome may occur during surgical procedures, for example, in long surgical procedures. Compartment syndrome may occur if surgery is performed in lithotomy position or lateral decubitus position. Compartment syndrome may include pressure buildup within muscles. Compartment syndrome may include pressure buildup within muscles that decreases blood flow and/or prevents oxygen from reaching nerve and/or muscle cells.

For example, the surgical computing system may determine parameters associated with operation of a visual display. The surgical computing system may obtain monitored data associated with one or more of a head or the eye position of an HCP. Based on the monitored data, the surgical computing system may determine parameters associated with operation of the visual display. The display operation parameters associated with the visual display may be generated based on monitored eye strain and/or monitored viewing position.

In examples, the surgical computing system may determine parameters for reducing eye strain. Improper monitor settings may lead to eye strain, eye fatigue, and/or headaches. An OR surveillance system, such as the HCP monitoring system described herein for example, may monitor eye motions and strain of an HCP during surgery. The surgical computing system may obtain monitored data associated with eye strain. Based on the monitored data, the surgical computing system may determine eye strain associated with the HCP. The surgical computing system may determine display operation parameter(s) associated with a visual display based on the monitored data associated with eye strain. The display operation parameters may include one or more of a setting or adjustment for brightness, color temperature, color contrast, or font associated with the visual display. The surgical computing system may determine display operation parameter(s) associated with one or more visual displays based on the determined eye strain associated with one or more HCPs.

For example, the surgical monitoring system may determine to enlarge a section of the display, implement a zoomed-in or zoomed-out view and/or increase the font of the display, and may send parameters to effectuate the determined adjustment(s).

The surgical monitoring system may, based on the received monitored data determine the direction that the HCP is looking, for example. The surgical monitoring system may identify, based on the received monitoring data that the HCP is looking at a particular portion of the display. The surgical computing system may determine to enlarge the identified portion of the display that the HCP is viewing.

For example, the surgical monitoring system may determine to enlarge a particular portion of the display based on eye strain. The surgical monitoring system may detect, based on the received monitored data that an HCP suffers from eye strain. Eye strain may be detected based on HCP squinting, moving closer to a monitor, increased blink rate, sclera (e.g., red eyes). Based on the determination, the surgical monitoring system may enlarge the identified portion of the display that the HCP is viewing to reduce eye strain. The surgical monitoring system may continue to enlarge the particular portion of the display until eye strain is reduced. The surgical monitoring system may determine to return the display to a normal or the default view upon determining that the HCP is viewing a different portion of the display or is looking away from the display. The surgical monitoring system may determine to return the display to a normal or the default view based on a task completion.

For example, the surgical computing system may determine display operation parameter(s) associated with the brightness of the display based on the energy level and/or fatigue level of the HCP. Details on energy level and fatigue level measurements are described in U.S. application Ser. No. 17/156,287 (attorney docket number END9290USNP1), titled METHOD OF ADJUSTING A SURGICAL PARAMETER BASED ON BIOMARKER MEASUREMENTS, filed Jan. 22, 2021, the disclosure of which is herein incorporated by reference in its entirety. Increasing the brightness of a monitor may reduce the flicker rate of the computer. Increasing the brightness of a monitor and/or reducing the flicker rate of a computer may reduce fatigue. A bright monitor may cause pupils to constrict. Constricted pupils may result in a greater range of focus. A greater range of focus may reduce the need for an eye to accommodate. A greater range of focus may enable an HCP to work longer and/or work with more comfort.

For example, the surgical computing system may determine display operation parameter(s) associated with monitor color temperature. The surgical computing system may determine the monitor color temperature based on the amount of light in the OR. In examples, the surgical computing system may determine to use a warmer color temperature in a dark room. A warmer color temperature may include a yellow-based color temperature. In examples, the surgical computing system may determine to use a colder color temperature in a bright room. A colder color temperature may include a blue-based color temperature.

For example, the surgical computing system may determine display operation parameter(s) associated with monitor contrast. Low contrast on a display and/or monitor may cause eye strain. Higher contrast on a display and/or monitor may reduce eye strain. In examples, a surgical computing system may determine to increase a monitor contrast based on monitored data indicating HCP eye strain.

For example, the surgical computing system may determine display operation parameter(s) associated with monitor font size(s). Small font size may cause eye strain. In examples, the surgical computing system may determine to increase a monitor font based on monitored data indicating HCP eye strain.

For example, the surgical computing system may determine display parameters associated with monitor position. Monitor position may be optimized for a surgical procedure. For example, the optimal view for a laparoscopy surgical procedure may include a monitor positioning at or within 15 to 40 degrees below the horizontal plane of the eye of the viewing HCP. A monitor positioning at 25 degrees below the horizontal plane of the eye of the viewing HCP may be optimal for a laparoscopy surgical procedure. The monitor positioning at or within 15 to 40 degrees or at 25 degrees below the horizontal plane of the eye of the viewing HCP may cause the least amount of neck strain. Adjusting surgical equipment to ergonomic needs of an HCP may minimize neck strain. The surgical computing system may determine, based on monitored data, if a monitor is not in a proper position. The surgical computing system may determine a proper angle for the monitor, for example, to suit the ergonomic needs of the HCP and may indicate the proper angle via the display parameter(s).

At 38122, the surgical computing system may communicate the parameters. The surgical computing system may communicate the parameters to one or more systems associated with the operating room. The surgical computing system may instruct a display to display the parameters, for example, to the HCP within the OR. The parameters may be included in recommendations or feedback for an OR layout. The parameters may be included in recommendations or feedback for operating a display. The parameters may be included in recommendations or feedback for operating or positioning surgical equipment and/or devices. The parameters may be included in recommendations or feedback for patient positioning. The parameters may be included in instructions for operation of surgical equipment. For example, the surgical computing system may communicate the parameters as part of instruments or control signal to surgical equipment. For example, the surgical computing system may communicate the parameters as part of instruments or control signal to a display. The surgical computing system may communicate a determined risk level and/or parameters associated with the risk level, such as surgical device positioning, for example, to a display.

At 38124, surgical equipment may receive parameters. Surgical equipment may receive parameters from the surgical computing system. Surgical equipment may include surgical instruments, surgical devices, surgical robots, surgical tables, an operating bed, and/or the like.

At 38126, surgical equipment may modify its operation. The surgical equipment may modify its operation based on parameters. The surgical equipment may modify its operation based on the parameters received from the surgical computing system. For example, an HCP using a surgical instrument may experience fatigue, such as a weakened grip on a surgical instrument trigger. The surgical computing system may determine, based on monitored data, parameters associated with reducing fatigue. The parameters may include increasing power to the surgical instrument. The surgical computing system may communicate the parameters to the surgical instrument. The surgical instrument may modify its operation such that the surgical instrument may output a higher power despite a weakened grip by the HCP.

At 38128, a display may receive parameters. The display may receive the parameters from the surgical computing system. The display may be a surgical display. The display may be a monitor. The display may be a part of a surgical hub as described herein. The display may be a part of the surgical computing system.

At 38130, the display may present parameters. The display may present the parameters, for example, received from the surgical computing device. For example, the display may present the parameters associated with patient positioning. The display may present an outline of the patient on the operating bed for the proper positioning of a patient for the surgical procedure.

The display may present one or more notifications configured to indicate suggested actions for HCPs to take. The suggested actions may include instructions for performing a surgical procedure or surgical plan. The suggested actions may include instructions for implementing ergonomic positioning within the OR. The suggested actions may include instructions to modify movement and/or posture for HCPs and/or a patient.

For example, the display may present parameters associated with HCP and/or surgical equipment positioning within the OR. In an example, the display may present parameters associated with one or more of table height, mayo stand placement and/or angle, or monitor position and/or angle. The display may present the parameters for the HCP to maintain a neutral position and/or minimize extension or flexion for reach and neck or back strain. The display may present recommendations to HCPs associated with a neutral and/or correct posture. The display may present recommendations throughout a surgical procedure.

For example, the display may present a risk level associated with a surgical procedure, for example, based on monitored data or historical data. The display may receive parameters and/or feedback associated with the risk level. The display may present the parameters and/or feedback associated with the risk level, for example, to HCPs within the OR. The display may use colors to indicate risk level. For example, a color may be associated with a particular risk level. In examples, a risk level determined to be good may be presented as green, a risk level determined to be low risk may be presented as yellow, and/or a risk level determined to be a high risk may be presented as red.

At 38132, the display may modify its operation. The display may modify its operation based on display operation parameters received from the surgical computing device, for example. The display may modify its operation based on display operation parameters associated with reducing eye strain. The display may modify its operation based on display operation parameters associated with ergonomic positioning, such as the positioning of the display.

For example, in response to receiving display operation parameters associated with reducing eye strain from the surgical computing system, the display may modify settings of the display. The display may modify the brightness, color temperature, color contrast, font and/or the like based on the received parameters. For example, the display may increase monitor brightness to reduce eye strain. The display may modify color temperature to reduce eye strain (e.g., to use warm color temperature in an environment with dark lighting, to use cool color temperature in an environment with bright lighting.

For example, the display may receive parameters associated with ergonomic positioning. The display may receive parameters associated with the positioning of the display. The display may receive parameters associated with the positioning of the display with respect to the HCP. The monitor may receive parameters associated with the positioning of the display for a surgical procedure.

For example, the display may modify its positioning to reduce wear on an HCP. The surgical computing system may receive monitored data associated with the head or eye position of the HCP. For example, the surgical computing system may receive monitored data, such as a picture, frame, video, and/or the like, from a camera or surveillance system in the OR. The surgical computing system may determine parameters associated with the position of a visual display, for example, based on the monitored data. For example, the surgical computing system may determine a position of the HCP, such as location within the OR and the HCP's head and eye position, and a display's position and orientation, based on the monitored data. The surgical computing system may determine the HCP's viewing angle of the display, for example, based on HCP location, HCP's head or eye position, and/or monitor position and orientation. Based on the determined viewing angle, the surgical computing system may determine adjustment parameters to modify the display positioning and orientation, for example, to improve motions and/or postures and/or reduce eye strain.

FIG. 33 illustrates an example display position within an operating room. As shown in FIG. 33 , an HCP 38210 may be performing a surgical procedure in an operating room at a surgical site 38212 on a patient. The HCP 38210, during the surgical procedure, may use a surgical display 38214. The position and/or orientation of the surgical display 38214 may be controlled by a multi-axis control arm 38216. As shown in FIG. 33 , a viewing angle 38218 may be the angle between the horizontal plane of the eyes of the HCP 38210 and the line of sight towards the surgical display 38214. The operating room may include a surveillance system 38220, which may include, for example, a camera. The surveillance system 38220 may monitor the position of the HCP 38210 and the surgical display 38214. The surveillance system 38220 may calculate the viewing angle 38218, for example, based on the monitored position of the HCP 38210 and the surgical display 38214. For example, the surveillance system 38220 may send the monitored position data to a surgical computing system, and the surgical computing system may calculate the viewing angle 38218 based on the position of the HCP 38210 and the surgical display 38214. Based on the viewing angle, the surgical computing system may determine whether the HCP 38210 is maintaining neutral posture and/or whether the surgical display 38214 is properly positioned. The surgical computing system may determine adjustment parameters for the surgical display, such as a modified position and/or orientation such that the viewing angle is ergonomic and/or improves the HCP's posture.

In examples, the surgical computing system may determine parameters associated with operation or a position of a visual display based on the surgical procedure. For example, in laparoscopic procedures, a display positioning where the display is at or within the range of 15 and 40 degrees below the horizontal plane of an eye of an HCP may minimize neck strain for the HCP. A display positioning where the display is at 25 degrees below the horizontal plane of the eye of the HCP may minimize neck strain for the HCP.

The surgical computing system may communicate the parameters associated with the display positioning to the display. The display may indicate to the OR team a notification based on the parameters. For example, the display may indicate to the OR team that the display is not in the correct position, for example, outside the range of 15 and 40 degrees below the horizontal plane of the eyes of an HCP in laparoscopic procedures. The display's position may be modified, for example, using a multi-axis control arm. The surgical computing system and/or HCP monitoring system may modify the display's position. The display's position may be modified based on determined adjustment parameters from the surgical computing system. The modified display position may minimize or reduce neck strain.

For example, the display may continuously receive parameters associated with ergonomic positioning of the display from the surgical computing system throughout a surgical procedure. The display may continuously modify its operation, for example, its positioning, based on the received parameters throughout the surgical procedure.

Tracking and adjusting a display may be performed. A display may be adjusted based on the HCP using the display and/or the HCP viewing the display. For example, monitor triangulation may be performed. Monitor triangulation with an HCP may be performed based on the head and eye motions of the HCP. Monitor positioning may be determined based on the head and eye motions of the HCP. A monitor positioning may be in an incorrect location, for example, not visible to an HCP using or viewing the display.

For example, the surgical computing system may determine one or more parameters associated with operation of a visual display.

The display may include a self-adjusting monitor. The display may allow a surgical computing system or surgical hub to change the position and/or angle of the monitor. The display may allow the surgical computing system or surgical hub to change the position and/or angle of the monitor to a surgeon using the system.

FIG. 34 illustrates an example operating room that includes a surveillance system monitoring head and eye positioning of healthcare professionals. As shown in FIG. 34 , an OR may be monitored using a camera. The camera may monitor the locations, positions, and/or orientations of HCP(s) within the operating room, such as HCP(s) location and/or angle relative to display. For example, the camera may monitor HCPs head or eye position and/or eye contact to the camera and/or display. The camera may send the monitored data to the surgical computing system. HCP(s) within the OR may have an HCP role or job associated with a surgical procedure. For example, as shown in FIG. 34 , the HCPs in the OR may be a primary surgeon 38252, an anesthesiologist 38254, a physician assistant 38256, or a nurse 38258.

As shown in FIG. 34 , HCP(s) ID and/or role may be determined, for example, using RF signals or facial recognition algorithms. The camera 38250 may monitor HCPs 38252, 38254, 38256, and 38258 within an OR. For example, the camera may use facial recognition algorithms to identify the HCPs within the OR. The camera 38250 may monitor (e.g., capture) the faces of the HCP(s) 38260, 38262, 38264, and 38266 within the OR. Based on the faces of the HCP(s), the camera may use facial algorithms to identify the HCPs. For example, the camera may receive RFID signals from an ID card 38268, 38270, 38272, and 38274 on the HCP(s). Based on the RFID signals, the camera may determine the HCP(s) ID and/or role. Based on the HCP(s) ID, the camera may determine the HCP(s) roles. For example, the camera may determine that HCP 38252 is the primary surgeon, HCP 38254 is the anesthesiologist, HCP 28256 is the physician assistant, and/or HCP 38258 is the nurse. The determinations described herein may be performed by the surgical computing system.

An HCP priority may be determined, for example, by the camera 38250 or a surgical computing system. The surgical computing system may determine an HCP priority, for example, based on a surgical procedure, a surgical procedure step, an HCP ID, an HCP role, and/or the like. For example, an anesthesiologist may have the highest HCP priority (e.g., a first priority), during a surgical procedure step associated with administering general anesthesia. For example, a primary surgeon, an anesthesiologist, a physician assistant, and a nurse may have different a priority based on the surgical procedure and/or step of the surgical procedure. For example, the primary surgeon may have the highest priority (e.g., first priority), the anesthesiologist may have the second highest priority (e.g., second priority), the physician assistant may have the third highest priority (e.g., third priority), and the nurse may have the fourth highest priority (e.g., fourth priority). The priority level may be associated with, for example, a priority for viewing a display.

FIG. 35 illustrates an example display in an operating room. As shown in FIG. 35 , the display 38300 may pivot positions and orientations, for example, between healthcare professionals. For example, the display 38300 may pivot from a first position and/or orientation 38302 to a second position and/or orientation 38304. The surgical computing system may determine to pivot the position and/or orientation of the display 38300, for example, based on determined display adjustment parameters associated with ergonomic positioning within the OR. The display adjustment parameters may be determined based on the HCP(s) present in an OR and/or the roles of the present HCP(s).

As shown in FIG. 35 , a first HCP 38306 and a second HCP 38308 may be present in an OR. A camera 38310 may monitor the first HCP 38306 and the second HCP 38308. The camera may send monitored data to the surgical computing system, and the surgical computing system may determine display adjustment parameters based on the monitored data. For example, the surgical computing system may determine a first angle of viewing 38312 associated with the first HCP 38306 and a second angle of viewing 38314 associated with the second HCP 38308. The surgical computing system may determine display adjustment parameters based on the first angle of viewing 38312 and the second angle of viewing 38314.

The surgical computing system may determine display adjustment parameters based on HCP priority, for example, if multiple HCPs are viewing the display. The surgical computing system may determine HCP priority based on an RFID signal on an HCP ID card 38316 and 38318 and/or facial recognition algorithms. For example, the surgical computing system may determine display adjustment parameters to pivot the display toward the higher priority HCP. If an anesthesiologist and a nurse are looking at the display, the surgical computing system may determine display adjustment parameters pivoting the position and orientation of the monitor to face the anesthesiologist, for example, if the anesthesiologist has a higher priority than the nurse. For example, the display adjustment parameters may be switching the display 38306 from the first position and/or orientation 38302 to the second position and/or orientation 38304, such that the higher priority HCP has an improved view. 

1. A method comprising: obtaining, at a surgical computing system, monitored data associated with movement of a plurality of surgical instruments in an operating room; determining, based at least in part on the monitored data, a parameter associated with a recommended surgical instrument within the operating room; and communicating the parameter associated with the recommended surgical instrument within the operating room.
 2. The method of claim 1, further comprising: communicating an indication of preparing the recommended surgical instrument for use.
 3. The method of claim 1, further comprising: determining procedure data associated with a surgical procedure plan in the operating room, wherein the parameter associated with the recommended surgical instrument is determined based at least in part on the monitored data and the procedure data.
 4. The method of claim 3, wherein the recommended surgical instrument is not specified for the surgical procedure plan.
 5. The method of claim 1, further comprising: obtaining monitored data associated with a plurality of instruments associated with the operating room; determining procedure data associated with a surgical procedure plan in the operating room; identifying, based on the procedure data, a surgical instrument anticipated for future use, wherein the recommended surgical instrument within the operating room comprises the identified surgical instrument anticipated for future use; and determining, based on the monitored data associated with the plurality of instruments associated with the operating room, a readiness of the identified surgical instrument anticipated for future use, wherein the parameter associated with the recommended surgical instrument comprises an indication to prepare the recommended surgical instrument for use.
 6. The method of claim 1, further comprising: obtaining procedure data associated with a surgical procedure plan in the operating room, determining, based at least in part on the monitored data and the procedure data, inactivity inconsistent with the surgical procedure plan; generating an indication of inactivity inconsistent with the plan for the surgical procedure; and communicating the indication of inactivity inconsistent with the plan for the surgical procedure.
 7. The method of claim 6, wherein the inactivity inconsistent with the plan for the surgical procedure comprises inactivity exceeding a time threshold.
 8. The method of claim 6, further comprising determining a recommendation associated with the inactivity inconsistent with the surgical procedure plan; and communicate the recommendation associated with inactivity inconsistent with the surgical procedure plan.
 9. A surgical computing system comprising: a processor configured to: obtain monitored data associated with movement of a plurality of surgical instruments in an operating room; determine, based at least in part on the monitored data, a parameter associated with a recommended surgical instrument within the operating room; and communicate the parameter associated with the recommended surgical instrument within the operating room.
 10. The surgical computing system of claim 9, wherein the processor is further configured to communicate an indication of preparing the recommended surgical instrument for use.
 11. The surgical computing system of claim 9, wherein the processor is further configured to: determine procedure data associated with a surgical procedure plan in the operating room, wherein the parameter associated with the recommended surgical instrument is determined based at least in part on the monitored data and the procedure data.
 12. The surgical computing system of claim 11, wherein the recommended surgical instrument is not specified for the surgical procedure plan.
 13. The surgical computing system of claim 9, wherein the processor is further configured to: obtain monitored data associated with a plurality of instruments associated with the operating room; obtain procedure data associated with a surgical procedure plan in the operating room; identify, based on the procedure data, a surgical instrument anticipated for future use, wherein the recommended surgical instrument within the operating room comprises the identified surgical instrument anticipated for future use; and determine, based on the monitored data associated with the plurality of instruments associated with the operating room, a readiness of the identified surgical instrument anticipated for future use, wherein the parameter associated with the recommended surgical instrument comprises an indication to prepare the recommended surgical instrument for use.
 14. The surgical computing system of claim 9, wherein the processor is further configured to: obtain procedure data associated with a surgical procedure plan in the operating room, determine, based at least in part on the monitored data and the procedure data, inactivity inconsistent with the surgical procedure plan; generate an indication of inactivity inconsistent with the surgical procedure plan; and communicate the indication of inactivity inconsistent with the surgical procedure plan.
 15. The surgical computing system of claim 14, wherein the inactivity inconsistent with the plan for the surgical procedure comprises inactivity exceeding a time threshold.
 16. The surgical computing system of claim 14, wherein the processor is further configured to: determine a recommendation associated with the inactivity inconsistent with the surgical procedure plan; and communicate the recommendation associated with inactivity inconsistent with the surgical procedure plan.
 17. A surgical computing system comprising: a processor configured to: obtain monitored data associated with emotions experienced by a plurality of healthcare professionals in an operating room; determine based at least in part on the monitored data, a parameter associated with altering emotions experienced by the plurality of healthcare professionals in the operating room; and communicate the parameter associated with altering emotions to one or more systems associated with the operating room.
 18. The surgical computing system of claim 17, wherein the processor is further configured to: obtain monitored data associated with stress experienced by the plurality of healthcare professionals, wherein the determined parameter is associated with an audio system or display system, and the determined parameter is communicated to the respective audio system or display system.
 19. The surgical computing system of claim 18, wherein the parameter associated with the audio system comprises a parameter associated with the audio system generating calming sounds, and wherein the parameter associated with the display system comprises a parameter associated with the display system generating calming output.
 20. The surgical computing system of claim 17, wherein the processor is further configured to: determine an adjustment associated with altering emotions experienced by the plurality of healthcare professionals in the operating room; and send a control signal based on the determined adjustment associated with altering emotions. 